Intelligent joint prosthesis

Abstract

To provide an intelligent joint prosthesis.SOLUTION: Medical devices coupled to a sensor, and systems including such medical devices, generate data and use the data to generate an analysis result, which may be used to identify and / or address problems associated with an implanted medical device, the problems including incorrect placement of the medical device, unanticipated degradation of the medical device, and undesired movement of the medical device. Also there are provided medical devices coupled to a sensor, and apparatuses and methods for addressing problems that have been identified with the implanted medical device.SELECTED DRAWING: Figure 41

Description

Technical Field

[0001] The present invention generally relates to medical devices equipped with sensors, systems including such devices, methods of using such devices and systems and the data generated therefrom, and devices and methods for addressing problems associated with implanted medical devices with sensors.

[0002]

Reference to Related Applications

Background Art

[0003] The use of medical devices and implants is customary in modern medicine. Typically, medical devices and implants are manufactured to replace, support, or strengthen anatomical or biological structures. When a medical device is placed on the surface of a patient's body, the device is readily visible to the patient and the attending healthcare professional or medical staff. However, when a medical device is designed to be implanted within a patient's body, i.e., an implantable medical device or medical implant, such a medical device is typically not readily visible.

[0004] Examples of medical implants include orthopedic implants such as hip replacements, shoulder replacements, and knee replacements, spinal implants (vertebral cages and artificial discs) and spinal hardware (screws, plates, pins, rods), intrauterine contraceptive devices, orthopedic hardware (casts, braces, tension bands, plates, screws, wires, dynamic hip screws, pins and plates) used to repair fractures and soft tissue injuries, cochlear implants, cosmetic surgical implants (breast implants, fillers), and dental implants.

[0005] Using the knee joint as a specific example, current artificial systems for total knee arthroplasty (TKA) typically consist of up to five components, namely, a femoral component, a tibial component, a tibial insert, a tibial stem extension, and a patellar component, and these five components together may be referred to as a total knee implant (TKI). These components are designed to work together as a functional unit to replace and provide the function of the native knee joint. The femoral component is attached to the femoral head of the knee joint to form the upper joint surface. The tibial insert (also called a spacer) is often composed of a polymer and, together with the metal femoral head, forms the lower joint surface. The tibial component consists of a tibial stem that enters the medullary cavity of the tibia and a baseplate, which may be referred to as a tibial plate, a tibial tray, or a tibial baseplate, depending on which one contacts / holds the tibial insert. Optionally, and particularly when the quality and / or bone mass of the proximal tibia is compromised, the tibial stem extension serves as a keel to increase stability by resisting the tilting of the tibial component. Examples of commercially available TKA products include the Persona™ knee joint system (I113369) and the associated tapered tibial stem extension (K133737), both of which are manufactured by Zimmer Biomet Inc. (Warsaw, Indiana, USA). The surgical procedure of implanting these four components into a patient's body is also called total knee replacement (TKR). Similar artificial devices are available for other joints, such as total hip arthroplasty (THA) and total shoulder arthroplasty (TSA), where one joint surface is metallic and the opposing surface is polymeric. These devices and procedures (TKA, THA, and TSA) are often collectively referred to as total joint arthroplasty (TJA).

[0006] Regarding TKA, the tibial component and the femoral component are typically inserted into the tibia and femur respectively and fixedly coupled therein. In some cases, these components are not fixedly coupled in place as in the case of the unconstrained knee joint. Regardless of whether these components are fixedly coupled in place, once placed and integrated into the surrounding bone (this process is called osseointegration), these components are not easily removable. Therefore, the proper placement of these components during implantation is extremely important for a successful outcome for each procedure, and the surgeon takes great care in implanting and fixing these components.

[0007] Current commercial TKA systems have a long history of clinical use, the implantation period is usually over 10 years, and according to some reports, an 87% survival rate has been demonstrated at 25 years. Clinicians currently monitor the progress of the implant postoperatively using a series of physical examinations at 2 - 3 weeks, 6 - 8 weeks, 3 months, 6 months, 12 months, and then annually.

[0008] After implanting the TKI and when the patient starts walking with the artificial knee joint, problems may occur, and such problems may be difficult to pinpoint. Clinical examinations are often limited in these abilities to detect prosthesis failures, and thus additional monitoring, such as CT scan methods, MRI scan methods, or even nuclear scan methods, are often required. Assuming that care requirements are continuously carried out throughout the lifespan of the implant, patients are encouraged to visit their regular doctor annually to check their health, monitor other joints, and have the functionality of the TKA implant evaluated. Current standards of care give doctors and the healthcare system the ability to evaluate the patient's TKA functionality during a 90-day episode of care, but the measurements are subjective and often lack the temporal resolution to depict slight changes in functionality that may be precursors to problems with significant mobility. Long-term (over 1 year) follow-up of TKA patients also poses the problem that patients do not consistently visit their regular doctor every year. Rather, TKA patients often only initiate separate consultations when they have pain or other symptoms. Summary of the Invention Problems to be Solved by the Invention

[0009] At present, there is no mechanism for highly reliably detecting TKA misplacement, instability, or malalignment without the skills and visual observation of clinical visiting doctors and skilled healthcare providers. Even in such cases, it is either difficult or impossible to detect pre-clinical problems or conditions early, because such pre-clinical problems or conditions are often extremely subtle and cannot be detected by physical examinations, or are often demonstrable by radiological examinations. Furthermore, even if detection is possible, corrective measures are hindered by the fact that the specific amount of movement and / or the degree of inappropriate alignment cannot be accurately measured or quantified, making the targeted successful intervention or treatment unlikely. External monitoring devices do not provide the fidelity necessary to detect instability, because these devices are separated from the TKA by skin, muscle, and fat (each of which masks mechanical traces of instability), and result in abnormalities such as flexion, tissue-bone acoustic noise, inconsistent sensor placement on the surface, and inconsistent placement locations of external sensors relative to the TKA.

[0010] Implants other than TKA implants may also be associated with various complications both during and after implantation. In general, accurately placing medical implants is a challenge for surgeons, and various complications can occur during the insertion of any medical implant (whether an open surgical procedure or a minimally invasive technique). For example, a surgeon may want to confirm the accurate anatomical alignment and placement of an implant within surrounding tissues and structures. However, this can be difficult to do during the performance of the procedure itself, thereby making accurate intraoperative adjustment difficult.

[0011] In addition, patients may suffer from numerous complications after the procedure. Such complications include neurological symptoms, pain, dysfunction (obstruction, laxity, etc.) and / or implant wear, implant movement or breakage, inflammation and / or infection. Some of these problems can be addressed with pharmaceuticals and / or additional surgery, but these are difficult to predict and prevent, and in many cases, early identification of complications and side effects is desirable but difficult or impossible.

[0012] The present invention aims to, in particular, identify these problems at an early stage, investigate and / or quantify the causes of the problems, and provide methods and devices or apparatuses for improving these problems.

[0013] All of the subject matter described in the Background of the Technology section is not necessarily prior art and should not be considered prior art simply as a result of the description in the Background of the Technology section. In accordance with these intentions, any recognition of problems in the prior art described in the Background of the Technology section or related to such subject matter should not be treated as prior art without an explicit indication that it is prior art. In contrast, the description of any subject matter in the Background of the Technology section should be treated as part of the inventor's approach to a particular problem, and such an approach may also, in essence and originally, be related to the invention.

Means for Solving the Problems

[0014] To summarize, the present invention relates to an intelligent implant, a system including the intelligent implant, a method for detecting, investigating, quantifying, and / or characterizing at least one of problems associated with an implant using the implant / system, and a method and device or apparatus for addressing the identified problems. As will be described in detail below, the present invention provides a medical device coupled to a sensor, and a system including such a medical device, which can generate data and analysis results based on the data, and such data can be used to identify and / or address problems associated with the implanted medical device. In one embodiment, the medical device is a prosthesis (TJA), and the data is kinematic data reflecting the movement of the prosthesis. Problems that can be identified include incorrect placement of the TJA instrument, incorrect alignment of the instrument, unexpected degradation or wear of the instrument, instability of the instrument (and associated joint), and undesirable movement of the instrument. Also provided are a medical device coupled to a sensor, and an apparatus and method for addressing problems identified with the implanted medical device.

[0015] A medical device coupled to a sensor may be referred to as an intelligent implant, in which case the intelligent implant has a sensor capable of detecting and / or measuring the performance of the implant function and / or the surrounding environment in the immediate vicinity of the implant and / or the activity / movement of the implant as well as the activity and movement of the patient. The implant may also be referred to as a prosthesis in another way, in which case the intelligent implant and the intelligent prosthesis have the same meaning. In one embodiment, coupling the sensor to a medical device, such as a prosthesis / implant, means disposing the sensor entirely within the medical device, so that the sensor is entirely surrounded by the outer surface of the medical device, and thus there is no part of the sensor that physically contacts any tissue of the patient into which the medical device is implanted. In embodiments of the present invention, when referring to a medical device or an implant or a prosthesis, these are understood to mean an intelligent medical device or an implant / prosthesis having a sensor disposed entirely within the medical device or implant / prosthesis disclosed herein. In embodiments of the present invention, herein, when referring to a medical device or an implant or a prosthesis having a sensor, this should be understood to mean an intelligent medical device or an implant / prosthesis in which the sensor is disposed entirely within the medical device or implant / prosthesis. In embodiments of the present invention, herein, when referring to a medical device or an implant or a prosthesis having a sensor, this should be understood to mean an intelligent medical device or an implant / prosthesis that is one accelerometer or two or more accelerometers (e.g., 2, 3, 4, 5, 6, 7, etc. accelerometers) in which the sensor is disposed entirely within the medical device or implant / prosthesis.In an embodiment of the present invention, in this specification, when referring to a medical device or an implant / prosthesis having a sensor, this should be understood to mean an intelligent medical device or an implant / prosthesis that is entirely disposed within the tibial extension of the medical device, implant / prosthesis, for example, one or more accelerometers (such as 2, 3, 4, 5, 6, 7, etc. accelerometers). Therefore, the medical device or implant / prosthesis is, for example, a component of a TKA.

[0016] The system includes an intelligent implant and one or more memories for storing data obtained from detection and / or measurement, an antenna for transmitting the data, a base station for receiving data generated by the sensor and transmitting this data and / or the analyzed data to a cloud-based storage location, a cloud-based storage location capable of storing and analyzing the data, and storing the analyzed data and / or further analyzing it, and a receiving station for receiving an output from the cloud-based storage location. This receiving station can be accessed, for example, by a healthcare professional or an insurance company or the manufacturer of the implant. The output can determine the status of the implant and / or the performance of the implant's function and / or the status of the patient who received the implant, and can also provide recommended measures for addressing any concerns arising from the analysis of the original data.

[0017] For example, due to the instability of arthroplasty (e.g., TKA, THA, and TSA) hardware, bone erosion and accelerated fatigue of implant components may occur. If left untreated or uncorrected, bone erosion and accelerated fatigue typically result in pain and inflammation. By the time the arthroplasty (TJA) patient is forced to seek medical care due to pain and inflammation, there may be only one option left for the healthcare professional, depending on the extent of bone erosion and TJA fatigue, namely, a highly invasive and costly surgery with a low likelihood of resulting in a "successful" outcome. The present invention provides an apparatus, system, and method that enable early detection of TJA hardware instability before damage occurs due to bone erosion and implant fatigue. This instability can be detected, quantified, and characterized, and the results communicated to the healthcare provider to enable early treatment and / or more effective management of the problem, i.e., the healthcare provider can utilize a corrective treatment that is far less invasive, less expensive, and has a high likelihood of success. The present invention also provides a device or apparatus and / or method for addressing the instability problem.

[0018] The present invention relates to TJA (total joint arthroplasty), which term includes surgery and related implanted hardware, such as the TJA prosthesis of the present invention. The features of the methods, devices, and systems of the present invention are described herein by reference to a particular intelligent TJA prosthesis, but the present invention is applicable to any one or more TJA prostheses including TKA (total knee arthroplasty) prostheses, such as TKI (total knee implant), sometimes also called a TKA system, TSA (total shoulder arthroplasty) prostheses, such as TSI (total shoulder implant), sometimes also called a TSI system, and THA (total hip arthroplasty) prostheses, such as THI (total hip implant), sometimes also called a THA system. In one embodiment, the TJA prosthesis is an intelligent TJA, also referred to as an intelligent TJA prosthesis having at least one sensor as disclosed herein.

[0019] The summary section of this invention is provided to introduce in simplified form certain inventive concepts that will be further described in detail below in the detailed description. Except as otherwise expressly stated, the summary section of this invention is not intended to identify key or essential features of the claimed subject matter, nor is it intended to limit the scope of the claimed subject matter.

[0020] The following are some numbered exemplary embodiments of the present invention. 〔Embodiment Item 1〕 A tibial insert for an implanted total knee joint, comprising a tibial insert having a thickness on the medial side of the implant that is 1 mm, 2 mm, 3 mm, 4 mm, 5 mm, 6 mm, 7 mm, 8 mm, 9 mm, or 10 mm thicker than the thickness on the lateral side of the implant. 〔Embodiment Item 2〕 A tibial insert for an implanted artificial knee joint, comprising a tibial insert in which the thickness on the outer (lateral) side of the implant is 1 mm, 2 mm, 3 mm, 4 mm, 5 mm, 6 mm, 7 mm, 8 mm, 9 mm, or 10 mm thicker than the thickness on the inner (medial) side of the implant. 〔Embodiment Item 3〕 A tibial insert for an implanted artificial knee joint, comprising a tibial insert in which the thickness on the front side of the implant is 1 mm, 2 mm, 3 mm, 4 mm, 5 mm, 6 mm, 7 mm, 8 mm, 9 mm, or 10 mm thicker than the thickness on the rear side of the implant. 〔Embodiment Item 4〕 A tibial insert for an implanted artificial knee joint, comprising a tibial insert in which the thickness on the rear side of the implant is 1 mm, 2 mm, 3 mm, 4 mm, 5 mm, 6 mm, 7 mm, 8 mm, 9 mm, or 10 mm thicker than the thickness on the front side of the implant. 〔Embodiment Item 5〕 A tibial insert or joint spacer for an implanted artificial knee joint, comprising a tibial insert in which the thickness of one of the inner (medial) side, outer (lateral) side, front side, and / or rear side of the implant is 1 mm, 2 mm, 3 mm, 4 mm, 5 mm, 6 mm, 7 mm, 8 mm, 9 mm, or 10 mm thicker than the thickness of the corresponding side of the implant. 〔Embodiment Item 6〕 The tibial insert according to any one of Embodiment Items 1 to 5, wherein the tibial insert is made of polyethylene or polyetheretherketone (PEEK). 〔Embodiment Item 7〕 The tibial insert according to any one of Embodiment Items 1 to 6, wherein the tibial insert is customized according to the patient. 〔Embodiment Item 8〕 The tibial insert according to any one of Embodiment Items 1 to 7, wherein the tibial insert is manufactured by 3D printing or molding. 〔Embodiment Item 9〕 An implantable medical device, comprising a circuit configured to be fixedly attached to an implantable artificial device, a power component, and a device configured to disconnect the circuit from the power component. 〔Embodiment Item 10〕 An implantable medical device, comprising a circuit configured to be fixedly attached to an implantable artificial device, a battery, and a fuse coupled between the circuit and the battery. 〔Embodiment Item 11〕 A method, comprising the step of electrically opening a fuse disposed between a circuit and a battery, wherein at least the fuse and the circuit are provided in an implantable artificial device. 〔Embodiment Item 12〕 An implantable medical device, comprising at least one sensor configured to generate a sensor signal, and a control circuit configured to generate the sensor signal at a frequency associated with a telemedicine code for the at least one sensor. 〔Embodiment Item 13〕 An implantable medical device, comprising at least one sensor configured to generate a sensor signal, and a control circuit configured to generate the sensor signal at a frequency that enables a physician to be eligible to pay for the at least one sensor under a telemedicine insurance code. 〔Embodiment Item 14〕 An implantable medical device, comprising at least one sensor configured to generate a sensor signal, and a control circuit configured to generate the sensor signal at a frequency that enables a physician to be eligible for full payment for the at least one sensor under a telemedicine insurance code. 〔Embodiment Item 15〕 A method, comprising the step of generating a sensor signal associated with an implantable medical device at a frequency that enables a physician to be eligible to pay for it under a telemedicine insurance code. Embodiment Item 16 A method, comprising the step of generating a sensor signal associated with an implantable medical device at a frequency that enables a physician to be eligible for full payment under a telemedicine insurance code. Embodiment Item 17 An implantable prosthesis, a housing, an implantable circuit disposed within the housing, and the implantable circuit is configured to generate at least one first signal representative of movement, determine whether the at least one first signal meets at least one first criterion, and send the at least one first signal to a remote location in response to a determination that the at least one first signal meets the at least one first criterion. Embodiment Item 18 A base station, a housing, a base station circuit disposed within the housing, and the base station circuit is configured to receive at least one first signal representative of movement from an implantable prosthesis, send the at least one first signal to a destination, receive at least one second signal from a source, and send the at least one second signal to the implantable prosthesis. Embodiment Item 19 A method, comprising the step of opening a fuse provided in an implantable prosthesis between a power source and an implantable circuit in response to a current passing through the fuse exceeding an overcurrent threshold. Embodiment Item 20 A method, comprising the step of opening a fuse provided in an implantable prosthesis between a power source and an implantable circuit in response to a current passing through the fuse exceeding an overcurrent threshold for at least a threshold time. 〔Embodiment Item 21〕 A method comprising the step of opening a fuse provided in an implantable prosthesis between a power source and an implantable circuit in response to a voltage applied across the fuse exceeding an overvoltage threshold. 〔Embodiment Item 22〕 A method comprising the step of opening a fuse provided in an implantable prosthesis between a power source and an implantable circuit in response to a voltage applied across the fuse exceeding an overvoltage threshold for at least a threshold time. 〔Embodiment Item 23〕 A method comprising the step of opening a fuse provided in an implantable prosthesis between a power source and an implantable circuit in response to a temperature exceeding an excessive temperature threshold. 〔Embodiment Item 24〕 A method comprising the step of opening a fuse provided in an implantable prosthesis between a power source and an implantable circuit in response to a temperature exceeding an excessive temperature threshold for at least a threshold length of time. 〔Embodiment Item 25〕 A method comprising generating a sensor signal in response to movement of a patient in whom a prosthesis is implanted and transmitting the sensor signal to a remote location. 〔Embodiment Item 26〕 A method comprising generating a sensor signal in response to movement of a patient in whom a prosthesis is implanted, sampling the sensor signal, and transmitting the sample to a remote location. 〔Embodiment Item 27〕 A method comprising generating a sensor signal in response to movement of a patient in whom a prosthesis is implanted, determining whether the sensor signal represents a qualifying event, and transmitting the sensor signal to a remote location in response to the determination of whether the sensor signal represents a qualifying event. 〔Embodiment Item 28〕 A method comprising Generating a sensor signal in response to the movement of a patient implanted with a prosthesis; receiving a polling signal from a remote location; and transmitting the sensor signal to the remote location in response to the polling signal. A method comprising the steps of: 〔Embodiment Item 29〕 A method comprising generating a sensor signal in response to the movement of a patient implanted with a prosthesis, creating a message including the sensor signal or data representing the sensor signal, and transmitting the message to a remote location. 〔Embodiment Item 30〕 A method comprising generating a sensor signal in response to the movement of a patient implanted with a prosthesis, generating a data packet including the sensor signal or data representing the sensor signal, and transmitting the data packet to a remote location. 〔Embodiment Item 31〕 A method comprising generating a sensor signal in response to the movement of a patient implanted with a prosthesis, encrypting at least a portion of the sensor signal or data representing the sensor signal, and transmitting the encrypted sensor signal to a remote location. 〔Embodiment Item 32〕 A method comprising generating a sensor signal in response to the movement of a patient implanted with a prosthesis, encoding at least a portion of the sensor signal or data representing the sensor signal, and transmitting the encoded sensor signal to a remote location. 〔Embodiment Item 33〕 A method comprising generating a sensor signal in response to the movement of a patient implanted with a prosthesis, transmitting the sensor signal to a remote location, and setting an implantable circuit associated with the prosthesis to a low power mode after transmission of the sensor signal. 〔Embodiment Item 34〕 A method, comprising: generating a first sensor signal in response to the movement of a patient with a prosthesis implanted; transmitting the first sensor signal to a remote location; setting at least one component of an implantable circuit associated with the prosthesis to a low-power mode after transmitting the sensor signal; and generating a second sensor signal in response to the movement of the patient after the elapse of a low-power mode time for which the implantable circuit is to be set. 〔Embodiment Item 35〕 A method, comprising: receiving a sensor signal from a prosthesis attached to or implanted in a patient; and transmitting the received sensor signal to a destination. 〔Embodiment Item 36〕 A method, comprising: sending an inquiry to a prosthesis attached to or implanted in a patient; after sending the inquiry, receiving a sensor signal from the prosthesis; and transmitting the received sensor signal to a destination. 〔Embodiment Item 37〕 A method, comprising: receiving a sensor signal and at least one identifier from a prosthesis attached to or implanted in a patient; determining whether the identifier is correct; and transmitting the received sensor signal to a destination in response to the determination of whether the identifier is correct. 〔Embodiment Item 38〕 A method, comprising: receiving a message including a sensor signal from a prosthesis attached to or implanted in a patient; decoding at least a part of the message; and transmitting the decoded message to a destination. 〔Embodiment Item 39〕 A method, comprising: receiving a message including a sensor signal from a prosthesis attached to or implanted in a patient; decrypting at least a part of the message; and transmitting the decrypted message to a destination. 〔Embodiment Item 40〕 A method comprising the steps of receiving a message including a sensor signal from a prosthesis attached to or implanted in a patient, encoding at least a portion of the message, and transmitting the encoded message to a destination. 〔Embodiment item 41〕 A method comprising the steps of receiving a message including a sensor signal from a prosthesis attached to or implanted in a patient, encrypting at least a portion of the message, and transmitting the encrypted message to a destination. 〔Embodiment item 42〕 A method comprising the steps of receiving a data packet including a sensor signal from a prosthesis attached to or implanted in a patient, decrypting at least a portion of the data packet, and transmitting the decrypted data packet to a destination. 〔Embodiment item 43〕 A method comprising the steps of receiving a data packet including a sensor signal from a prosthesis attached to or implanted in a patient, decoding at least a portion of the data packet, and transmitting the decoded data packet to a destination. 〔Embodiment item 44〕 A method comprising the steps of receiving a data packet including a sensor signal from a prosthesis attached to or implanted in a patient, encoding at least a portion of the data packet, and transmitting the encoded data packet to a destination. 〔Embodiment item 45〕 A method comprising the steps of receiving a data packet including a sensor signal from a prosthesis attached to or implanted in a patient, encrypting at least a portion of the data packet, and transmitting the encrypted data packet to a destination. 〔Embodiment item 46〕 A method comprising receiving a sensor signal from a prosthesis attached to or implanted within a patient, decoding at least a portion of the sensor signal, and transmitting the decoded sensor signal to a destination. 〔Embodiment item 47〕 A method comprising receiving a sensor signal from a prosthesis attached to or implanted within a patient, decrypting at least a portion of the sensor signal, and transmitting the decrypted sensor signal to a destination. 〔Embodiment item 48〕 A method comprising receiving a sensor signal from a prosthesis attached to or implanted within a patient, encoding at least a portion of the sensor signal, and transmitting the encoded sensor signal to a destination. 〔Embodiment item 49〕 A method comprising receiving a sensor signal from a prosthesis attached to or implanted within a patient, encrypting at least a portion of the sensor signal, and transmitting the encrypted sensor signal to a destination. 〔Embodiment item 50〕 An implantable circuit for an implantable prosthesis. 〔Embodiment item 51〕 An implantable prosthesis having an implantable circuit. 〔Embodiment item 52〕 An implantable prosthesis having a fuse. 〔Embodiment item 53〕 A base station capable of communicating with an implantable prosthesis. 〔Embodiment item 54〕 A monitoring-session-data collection, analysis, and status reporting system embodied as a component of one or more computer systems, each computer system including access to one or more processors, one or more memories, one or more network connection means, and one or more mass storage devices, the one or more monitoring-session-data collection, data analysis, and status reporting systems including a monitoring-session-data receiving component that receives monitoring-session-data including acceleration data generated by a sensor attached to a patient or implanted within or near a prosthesis of the patient from an external monitoring-session-data source and stores the received monitoring-session-data in the one or more memories and the one or more mass storage devices, including a monitoring-session-data processing component, the monitoring-session-data processing component preparing the monitoring-session-data for processing, determining a component trajectory representing a motion mode and additional metric values from the monitoring-session-data, including a monitoring-session-data analysis component, the monitoring-session-data analysis component determining the state of the prosthesis and the state of the patient from the motion mode and the additional metric values, distributing the determined prosthesis state and patient state to a target computer system via the network connection means, and distributing one or more warnings and events to the target computer system via the network connection means when indicated by the determined prosthesis state and patient state, a monitoring-session-data collection, analysis, and status reporting system. [[Embodiment Item 55]] The monitoring-session-data is a monitoring-session-data collection, analysis, and status reporting system according to Embodiment Item 54, including a patient identifier, an instrument identifier, a time stamp, device configuration data, and an ordered set of data. [Embodiment Item 56] The above ordered set of data is a time series of data-vectors each including numerical values associated with linear acceleration with respect to three coordinate axes of an internal device coordinate system, and a monitoring-session-data collection, analysis, and status reporting system according to Embodiment Item 55, including one of a time series of data-vectors each including numerical values associated with linear acceleration with respect to three coordinate axes of a first internal device coordinate system and numerical values associated with angular velocity, and numerical values associated with angular velocity with respect to the first internal device coordinate system or a second internal device coordinate system. [Embodiment Item 57] The monitoring-session-data processing component receives a time series of data-vectors each including three numerical values associated with linear acceleration in the directions of three coordinate axes of a first internal device coordinate system and three numerical values associated with angular velocity around each axis of the first or second internal device coordinate system, when rescaling of the data-vector series is required, scales the numerical values of the data-vector, when normalization of the data-vector series is required, normalizes the numerical values of the data-vector, when conversion of one or more of the numerical values associated with the linear acceleration and the numerical values associated with the angular velocity is required to associate the numerical values associated with the linear acceleration and the numerical values associated with the angular velocity with a common internal coordinate system, converts one or more of the numerical values associated with the linear acceleration and the numerical values associated with the angular velocity to associate them with the common internal coordinate system, and If the time series of the data-vector needs to be synchronized with respect to a fixed-interval time series, the monitoring-session-data collection, analysis, and status reporting system according to Embodiment Item 54, which prepares the monitoring-session-data for processing by synchronizing the data-vector with respect to the fixed-interval time series. [Embodiment Item 58] The monitoring-session-data processing component Orients the prepared monitoring-session-data having a data-vector that includes three numerical values each associated with the linear acceleration in the directions of the three coordinate axes of the internal device coordinate system and three numerical values each associated with the angular velocity around each axis of the internal device coordinate system, with respect to the natural coordinate system. Band-pass filters the oriented data-vector to obtain a set of data-vectors for each of a number of frequencies including the normal motion frequency. Determines the spatial amplitude in each of the coordinate axis directions of the natural coordinate system from the data-vector for each of the abnormal motion frequencies. Determines the spatial amplitude in each of the coordinate axis directions of the natural coordinate system from the basic trajectory for the patient and the data-vector for the normal motion frequency, and Determines the current normal motion characteristics from the basic trajectory for the patient and the data-vector for the normal motion frequency. The monitoring-session-data collection, analysis, and status reporting system according to Embodiment Item 54, which determines the component trajectories representing the motion mode and additional metric values from the monitoring-session-data. [Embodiment Item 59] The step of obtaining the spatial amplitude in each of the coordinate axis directions of the natural coordinate system from the data-vector regarding frequency further includes a step of generating a spatial locus from the data-vector, a step of projecting the spatial frequency onto each of the coordinate axes, and a step of obtaining the projection length of the spatial frequency onto each of the coordinate axes, for the monitoring-session-data collection, analysis, and status reporting system described in Embodiment Item 58. 〔Embodiment Item 60〕 The monitoring-session-data analysis component determines the prosthesis state and the patient state from the motion mode and the additional metric values. Submit the motion mode and the additional metric values to a decision tree that generates a diagnosis-and-suggestion report. Package the diagnosis-and-suggestion report together with the amplitude generated for the motion mode, the metrics generated from the normal motion frequency locus and the basic locus, and one or both of the output report and the output data value characterizing the prosthesis state and the patient state, to determine, for the monitoring-session-data collection, analysis, and status reporting system described in Embodiment Item 54. 〔Embodiment Item 61〕 The one or more warnings and events distributed to the target computer system by the monitoring-session-data analysis component are Include a warning notifying a doctor or a medical facility that the patient requires immediate assistance or intervention. Include events indicating additional care and / or equipment required by the patient, where the additional care and / or equipment can be handled by various external computer systems to automatically provide the additional care and / or equipment to the patient or notify the patient of the additional care and / or equipment and provide information regarding the acquisition of the additional care and / or equipment to the patient, for the monitoring-session-data collection, analysis, and status reporting system described in Embodiment Item 54. 〔Embodiment Item 62〕 A method implemented by a monitoring - session - data collection, analysis, and status reporting system embodied as components of one or more computer systems, where each computer system includes one or more processors, one or more memories, one or more network connection means, and access to one or more mass storage devices, and the method includes: Receiving monitoring - session - data including acceleration data generated by sensors attached to a patient or implanted within or proximate to a prosthesis implanted within the patient from an external monitoring - session - data source; Storing the received monitoring - session - data in one or more of the one or more memories and the one or more mass storage devices; Deriving the state of the prosthesis and the state of the patient from the motion mode and additional metric values; Delivering the derived prosthesis state and patient state to a target computer system via the network connection means; Delivering one or more warnings and events to the target computer system via the network connection means when indicated by the derived prosthesis state and patient state. The step of deriving the prosthesis state and the patient state from the motion mode and the additional metric values includes: Preparing the monitoring - session - data for processing; Determining component trajectories representing the motion mode and additional metric values from the monitoring - session - data; Submitting the motion mode and the additional metric values to a decision tree that generates a diagnostic and advisory report; The step of packaging the diagnostic and advisory report, together with additional metric values that result in one or both of an output report and output data values characterizing the amplitude resulting from the above-described motion mode, the normal motion frequency trajectory, and the metrics resulting from the basic trajectory, and the above-described prosthesis state and the above-described patient state, as described in embodiment item 62. [Embodiment item 64] The step of preparing the above monitoring-session-data for processing is Receiving a time series of data-vectors, each containing three numerical values associated with the linear acceleration in the directions of the three coordinate axes of the first internal device coordinate system and three numerical values associated with the angular velocity about each axis of the first or second internal device coordinate system; When rescaling of the above data-vector series is required, the step of rescaling the above numerical values of the data-vector; When normalization of the above data-vector series is required, the step of normalizing the above numerical values of the data-vector; When one or more conversions of the above numerical values associated with the linear acceleration and the above numerical values associated with the angular velocity are required to associate the above numerical values associated with the linear acceleration and the above numerical values associated with the angular velocity with a common internal coordinate system, the step of converting one or more of the above numerical values associated with the linear acceleration and the above numerical values associated with the angular velocity to associate them with the above common internal coordinate system; When the above time series of data-vectors needs to be synchronized with a fixed interval time series, the step of synchronizing the above data-vectors with respect to the fixed interval time series, further comprising the method described in embodiment item 62. [Embodiment item 65] The step of obtaining the motion mode and component trajectories representing additional metric values from the above monitoring-session-data is Orienting the prepared monitoring - session - data having a data - vector that includes three numerical values each associated with the linear acceleration in the above directions of the three coordinate axes of the internal device coordinate system and includes three numerical values each associated with the angular velocity about each axis of the internal device coordinate system with respect to the natural coordinate system; Band - pass filtering the oriented data - vector to obtain a set of data - vectors for each of a number of frequencies including the normal - motion frequency; Determining the spatial amplitude in each of the coordinate - axis directions of the natural coordinate system from the data - vectors for each of the abnormal - motion frequencies; Determining the spatial amplitude in each of the coordinate - axis directions of the natural coordinate system from the basic trajectory of the patient and the data - vectors for the normal - motion frequency; Determining the current normal - motion characteristics from the basic trajectory of the patient and the data - vectors for the normal - motion frequency, the method according to embodiment item 62 further comprising. 〔Embodiment item 66〕 The step of determining the spatial amplitude in each of the coordinate - axis directions of the natural coordinate system from the data - vectors for the frequency Generating a spatial trajectory from the data - vectors; Projecting the spatial frequency onto each of the coordinate axes; Determining the projection length of the spatial frequency onto each of the coordinate axes, the method according to embodiment item 62 further comprising. 〔Embodiment item 67〕 The step of deducing the prosthesis state and the patient state from the motion mode and the additional metric value Submitting the motion mode and the additional metric value to a decision tree that generates a diagnostic and suggestive report; The step of packaging the diagnostic and advisory report, together with additional metric values that result in one or both of an amplitude resulting from the above-described motion mode, a metric resulting from a normal motion frequency trajectory and a basic trajectory, and an output report and output data value characterizing the above-described prosthesis state and the above-described patient state, the method according to embodiment item 62, further comprising. [Embodiment item 68] The one or more warnings and events distributed to the target computer system by the monitoring-session-data analysis component are Including a warning notifying a physician or medical facility that the patient requires immediate assistance or intervention, Including events instructing additional care and / or equipment required by the patient, the additional care and / or equipment being handled by various external computer systems to automatically provide the additional care and / or equipment to the patient or to notify the patient of the additional care and / or equipment and provide information regarding the acquisition of the additional care and / or equipment to the patient, the method according to embodiment item 62. [Embodiment item 69] A physical data storage device encoded with computer instructions, the computer instructions, when executed by one or more processors provided within one or more computer systems of a monitoring-session-data collection, analysis, and status reporting system, cause each computer system including access to one or more processors, one or more memories, one or more network connection means, and one or more mass storage devices to A physical data storage device that controls the monitoring-session-data collection, analysis, and status reporting system to receive monitoring-session-data including acceleration data generated by a sensor provided within or proximate to a prosthesis attached to or implanted within a patient. [Embodiment item 70] A method for detecting joint laxity in a patient with an implanted artificial joint, the method comprising: a) analyzing the movement of the implanted artificial joint; and b) comparing the movement with a previous / standardized reference. 〔Embodiment item 71〕 A method for detecting loosening of an implanted prosthesis in a patient in whom a prosthesis has been implanted, a) obtaining a standardized reference of movement by analyzing the movement of the implanted prosthesis during one or more first monitoring sessions; b) obtaining the current content of movement by analyzing the movement of the implanted prosthesis during one or more second monitoring sessions following the one or more first monitoring sessions; c) comparing the current content of movement with the standardized reference of movement, thereby detecting loosening of the implanted prosthesis in a patient with the implanted prosthesis. 〔Embodiment item 72〕 A method for detecting a clinical or pre-clinical condition associated with an implant in a patient, the method comprising: a. monitoring a first movement of the implant during a first monitoring session using a sensor directly coupled to the implant to provide first monitoring-session data regarding the first movement; b. monitoring a second movement of the implant during a second monitoring session using the sensor to provide second monitoring-session data regarding the second movement; c. comparing the first monitoring-session data or a processing result thereof with the second monitoring-session data or a processing result thereof to provide a comparison result representing a clinical or pre-clinical condition associated with the implant. 〔Embodiment item 73〕 The clinical or pre-clinical condition is, as an option, the loosening of the implant due to a lucency around the prosthesis or osteolysis around the prosthesis, the method according to embodiment item 72. 〔Embodiment item 74〕 The clinical or pre-clinical condition is a misalignment of the implant (suboptimal positioning of the prosthesis component) or readjustment (change in the alignment of the prosthesis component), the method according to embodiment item 72. 〔Embodiment item 75〕 The clinical or pre-clinical condition is a deformation (wear) of the implant, the method according to embodiment item 72. 〔Embodiment item 76〕 The patient is asymptomatic with respect to the clinical or pre-clinical condition, and from the comparison result of the first and second data or the processing result of the data, it can be seen that the condition has likely occurred between the first monitoring session and the second monitoring session, the method according to embodiment item 72. 〔Embodiment item 77〕 The patient is asymptomatic with respect to the loosening of the implant, and from the comparison result of the first and second data or the processing result of the data, it can be seen that the implant has likely loosened between the first monitoring session and the second monitoring session, the method according to embodiment item 72. 〔Embodiment item 78〕 The patient is asymptomatic with respect to the readjustment of the implant, and from the comparison result of the first and second data or the processing result of the data, it can be seen that the implant has likely changed its alignment between the first monitoring session and the second monitoring session, the method according to embodiment item 72. 〔Embodiment item 79〕 The patient is asymptomatic with respect to the deformation of the implant, and from the comparison result of the first and second data or the processing result of the data, it can be seen that the implant is likely to have deformed between the first monitoring session and the second monitoring session, according to the method described in embodiment item 72. 〔Embodiment item 80〕 A method for treating a clinical or pre-clinical condition associated with an implant in a patient's body, comprising: a. identifying an implant in the patient's body, the implant presenting a clinical or pre-clinical condition; b. attaching a corrective external bracing to the patient to restore proper alignment and / or improved stability with respect to the implant. 〔Embodiment item 81〕 The method according to embodiment item 80, wherein the corrective external bracing is specially customized according to the patient and the pre-clinical condition. 〔Embodiment item 82〕 A method for treating a clinical or pre-clinical condition associated with an implant in a patient's body, comprising: a. identifying an implant in the patient's body, the implant presenting a clinical or pre-clinical condition; b. contacting the implant with a fixation system to slow the progression of the pre-clinical condition. 〔Embodiment item 83〕 The method according to embodiment item 82, wherein the fixation system includes hardware selected from K-wires, pins, screws, plates, and intramedullary devices. 〔Embodiment item 84〕 The screw for holding the implant is disposed through the bone, and the end of the screw presses against the surface of the implant to prevent the movement of the implant. The screw is selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, and 20 screws. The method according to embodiment item 82. 〔Embodiment item 85〕 The above fixation system is the method according to embodiment item 82, including bone cement. 〔Embodiment item 86〕 A method for treating a clinical or pre-clinical condition associated with an implant in a patient's body, a. including the step of identifying an implant in the patient's body, the implant presenting a clinical or pre-clinical condition, b. including the step of contacting a tamp, the contact changing the location of the implant in the patient's body, and optionally, c. applying cement around the implant with the changed location. 〔Embodiment item 87〕 The method according to embodiment item 86, wherein the pre-clinical condition is readjustment of the implant. 〔Embodiment item 88〕 A method for treating a clinical or pre-clinical condition associated with an implant in a patient's body, a. including the step of identifying an implant in the patient's body, the implant presenting a clinical or pre-clinical condition, b. including the step of implanting an insert adjacent to a component of the implant, the insert adjusting the force acting on the component of the implant. 〔Embodiment item 89〕 The method according to embodiment item 88, wherein the insert is a tibial insert. 〔Embodiment item 90〕 The method according to embodiment item 88, wherein the insert is a tibial insert having (i) an outer side with a minimum thickness and (ii) an inner side with a minimum thickness different from the minimum thickness of the outer side. 〔Embodiment item 91〕 A method for treating a clinical or pre-clinical condition associated with an implant in a patient's body, a. including the step of identifying an implant in the patient's body, the implant presenting a clinical or pre-clinical condition, b. A method comprising the step of delivering a pre-osseointegration agent to a location around the implant. [Embodiment item 92] The method according to embodiment item 91, wherein the pre-osseointegration agent is selected from autologous bone graft, heterologous bone graft, synthetic bone graft, bone paste, bone growth factor, and growth factor. [Embodiment item 93] A method for treating a clinical or pre-clinical condition associated with an implant in a patient's body, a. comprising the step of identifying an implant in the patient's body, the implant presenting a clinical or pre-clinical condition, b. A method comprising the step of delivering an antibacterial agent to a location around the implant. [Embodiment item 94] The method according to embodiment item 93, wherein the antibacterial agent is formulated in a sustained release form. [Embodiment item 95] The method according to any one of embodiment items 72 to 94, wherein the implant is an intelligent implant. [Embodiment item 96] The method according to any one of embodiment items 72 to 94, wherein the implant is selected from a knee joint implant, a hip joint implant, and a shoulder joint implant. [Embodiment item 97] The method according to any one of embodiment items 72 to 94, wherein the processing result of the monitoring-session-data consists of a motion mode. [Embodiment item 98] The method according to any one of embodiment items 72 to 94, wherein the processing result of the monitoring-session-data consists of a motion mode, and the state of the implant is deduced from the motion mode. [Embodiment item 99] The method according to any one of embodiment items 72 to 94, wherein the processing result of the monitoring-session-data consists of a motion mode, and the state of the patient is deduced from the motion mode. [Embodiment item 100] The implant is placed in the patient's body at least 10 weeks prior to the first monitoring session, and is the method according to any one of Embodiment Items 72 to 94. 〔Embodiment Item 101〕 The implant is the method according to any one of Embodiment Items 72 to 94, which changes the alignment over a period of at least two weeks. 〔Embodiment Item 102〕 The implant is the method according to any one of Embodiment Items 72 to 94, which relaxes over a period of at least two weeks. 〔Embodiment Item 103〕 The implant is the method according to any one of Embodiment Items 72 to 94, which deforms over a period of at least two weeks. 〔Embodiment Item 104〕 The implant has a control circuit configured to cause the sensor to generate a sensor signal at a frequency associated with a telemedicine code regarding the clinical or pre-clinical condition, and is the method according to any one of Embodiment Items 72 to 94. 〔Embodiment Item 105〕 The implant has a control circuit configured to cause the sensor to generate a sensor signal at a frequency that enables a doctor to be eligible for payment under a telemedicine insurance code, and the sensor signal occurs at the frequency, and is the method according to any one of Embodiment Items 72 to 94. 〔Embodiment Item 106〕 The implant has a control circuit configured to cause the sensor to generate a sensor signal at a frequency that enables a doctor to be eligible for full payment under a telemedicine insurance code, and the sensor signal occurs at the frequency, and is the method according to any one of Embodiment Items 72 to 94. 〔Embodiment Item 107〕 (i) The doctor has the qualification for full payment available under the telemedicine insurance code, or (ii) The method according to any one of embodiments 72 to 94 further includes the step of generating a sensor signal associated with the implant at a frequency that enables the doctor to have the qualification for payment available under the telemedicine insurance code. 〔Embodiment Item 108〕 A method comprising: a. Preparing an intelligent prosthesis implanted in a bone adjacent to a joint of a patient, wherein an accelerometer is housed within the intelligent prosthesis, and the accelerometer is positioned within the bone; b. Moving the implanted intelligent prosthesis with respect to an external environment, wherein the patient is positioned at a location where the implanted intelligent prosthesis is moved during a first monitoring session; c. During the first monitoring session, performing a first measurement with the accelerometer, the first measurement providing first monitoring-session-data or a processing result thereof that identifies the state of the implanted intelligent prosthesis at the time of the first measurement. 〔Embodiment Item 109〕 The method according to embodiment 108, wherein the accelerometer is a plurality of accelerometers. 〔Embodiment Item 110〕 The method according to embodiment 108, wherein the accelerometer is selected from a uniaxial accelerometer, a biaxial accelerometer, and a triaxial accelerometer. 〔Embodiment Item 111〕 The method according to embodiment 108, wherein the accelerometer operates in a broadband mode. 〔Embodiment Item 112〕 The method according to embodiment 108, wherein the bone is the tibia. 〔Embodiment Item 113〕 The method according to embodiment 108, wherein the accelerometer is disposed within a tibial extension of the intelligent prosthesis. 〔Embodiment Item 114〕 The implanted intelligent prosthesis is moved relative to the external environment without an impact being applied to the patient or the intelligent prosthesis during the first monitoring session, according to the method described in embodiment item 108. 〔Embodiment item 115〕 The external environment consists of the patient's residence, according to the method described in embodiment item 108. 〔Embodiment item 116〕 The external environment consists of an operating room, and the intelligent prosthesis is implanted in the patient's body, according to the method described in embodiment item 108. 〔Embodiment item 117〕 The state of the implanted intelligent prosthesis is an evaluation of the relaxation characteristics of the implanted intelligent prosthesis within the bone, according to the method described in embodiment item 108. 〔Embodiment item 118〕 The state of the implanted intelligent prosthesis is an evaluation of the alignment characteristics of the implanted intelligent prosthesis within the bone, according to the method described in embodiment item 108. 〔Embodiment item 119〕 The state of the implanted intelligent prosthesis is an evaluation of the wear characteristics of the implanted intelligent prosthesis, according to the method described in embodiment item 108. 〔Embodiment item 120〕 The state of the implanted intelligent prosthesis is an evaluation of the bacterial infection characteristics of the bone region located adjacent to the implanted intelligent prosthesis, according to the method described in embodiment item 108. 〔Embodiment item 121〕 The state of the implanted intelligent prosthesis indicates a pre-clinical state, according to the method described in embodiment item 108. 〔Embodiment item 122〕 Step b) is repeated after the waiting period, and the repetition of step b) includes moving the implanted intelligent prosthesis relative to the external environment in which the patient is located. The implanted intelligent prosthesis is moved during a second monitoring session, and a second measurement is performed with the accelerometer during the second monitoring session. The second measurement provides second monitoring-session-data or a second monitoring-session-data processing result that identifies the state of the implanted intelligent prosthesis at the second measurement time point. The method according to embodiment item 108. 〔Embodiment item 123〕 Step b) is repeated a plurality of times, the plurality of times being separated from each other by the same or different waiting periods. The repetition of step b) includes moving the implanted intelligent prosthesis relative to the external environment in which the patient is located. The implanted intelligent prosthesis is moved during a plurality of monitoring sessions, and measurements are performed with the accelerometer between each of the plurality of monitoring sessions. The measurements provide a plurality of monitoring-session-data or a processing result of the plurality of monitoring-session-data, each of which identifies the state of the implanted intelligent prosthesis at the measurement time point. The method according to embodiment item 108. 〔Embodiment item 124〕 Step b) is repeated a plurality of times, the plurality of times being separated from each other by only the same or different waiting periods, and the repetition of step b) includes moving the implanted intelligent prosthesis with respect to the external environment in which the patient is located, the implanted intelligent prosthesis being moved during a plurality of monitoring sessions, measurements being taken with the accelerometer between each of the plurality of monitoring sessions, the measurements providing a plurality of monitoring-session-data or a processing result of a plurality of monitoring-session-data, each identifying the state of the implanted intelligent prosthesis at the time of measurement, the plurality of monitoring-session-data being optionally selected from 2 to 20 monitoring sessions, the plurality of monitoring-session-data, when considered together, indicating a change in the state of the implanted intelligent prosthesis during the time when the plurality of monitoring sessions took place, according to the method of embodiment item 108. 〔Embodiment item 125〕 The change in the state represents the healing state of the tissue around the implanted intelligent prosthesis, according to the method of embodiment item 124. 〔Embodiment item 126〕 The change in the state represents the infection state of the tissue around the implanted intelligent prosthesis, according to the method of embodiment item 124. 〔Embodiment item 127〕 The change in the state represents the loosening of the implanted intelligent prosthesis within the bone, according to the method of embodiment item 124. 〔Embodiment item 128〕 The change in the state represents the wear of the implanted intelligent prosthesis, according to the method of embodiment item 124. 〔Embodiment item 129〕 The change in the state represents a misalignment of the implanted intelligent prosthesis, according to the method of embodiment item 124. 〔Embodiment item 130〕 The method according to embodiment item 124, wherein the change in the above state represents a change in the alignment of the implanted intelligent prosthesis.

[0021] Details of one or more embodiments are described in the following description. Features illustrated or described in connection with one exemplary embodiment can be combined with features of other embodiments. Thus, any combination of the various embodiments described herein can provide another embodiment. Aspects of such embodiments can be modified if necessary and concepts of various patents, various applications, and various patent application publications described herein can be adopted to provide yet another embodiment. Other features, other objects, and other advantages will become apparent from the specification text, the drawings, and the claims.

[0022] Exemplary features of the present invention, its nature, and various advantages will become apparent from the accompanying drawings and the following detailed description of various embodiments. Non-limiting and non-exhaustive embodiments are described with reference to the accompanying drawings, in which the same label or reference numeral indicates the same part throughout the various figures unless otherwise specified. The dimensions and relative positions of the elements in the drawings are not necessarily drawn to scale. For example, the shapes of the various elements are selected to make the drawings easy to view, enlarged, and arranged. The specific shapes of the elements depicted are selected to facilitate recognition of the drawings. Hereinafter, one or more embodiments will be described with reference to the accompanying drawings.

Brief Description of the Drawings

[0023]

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DETAILED DESCRIPTION OF THE INVENTION

[0024] The present invention can be easily understood by referring to the following detailed description of the preferred embodiments of the present invention and the examples of the "intelligent prosthesis" described herein. The following description, together with the accompanying drawings, describes certain details, and its purpose is to provide a complete understanding of the various disclosed embodiments. However, as will be recognized by those skilled in the art, the disclosed embodiments can be implemented in various combinations without one or more of these specific details or using other methods, other components, other devices, other materials, etc. In other cases, well-known structures or components related to the environment of the present invention (including, but not limited to, communication systems and networks) are not illustrated or described in order to avoid explanations that would unnecessarily obscure the embodiments. Additionally, the various embodiments can be various methods, various systems, various media, or various instruments. Therefore, the various embodiments can be entirely hardware embodiments, entirely software embodiments, entirely firmware embodiments, or embodiments that combine or partially combine the perspectives of software, firmware, and hardware.

[0025] Before describing the present invention in detail, it can be said that providing definitions of certain terms to be used in this specification will be helpful for understanding the present invention. Additional definitions are set forth throughout the present disclosure. The terms "include" (often translated as "comprising" in the translated text), "comprise" (often translated as "having" in the translated text), and their derivatives in the original specification mean inclusion without limitation. The term "or" is inclusive and means "and / or". The phrases "associated with" and "associated therewith" and their derivatives may mean "including", "included within", "interconnected with", "accommodating", "accommodated within", "connected to or connected with", "coupled to or coupled with", "capable of communicating with", "cooperating with", "alternately arranged", "juxtaposed", "located near", "bound to or bound with", "having", "having the characteristics of", etc. The term "controller" means any device, system, or part thereof that controls at least one operation, and such device can be embodied in a state of hardware (e.g., electronic circuit), firmware, software, or a combination of at least two of these. The functionality associated with any particular controller may be centrally or distributively managed, whether within the premises or remotely. Other definitions of certain terms and phrases may be provided in this specification. As will be understood by those skilled in the art, in many cases (if not most), such definitions will apply to the conventional and future use of such defined terms and phrases.

[0026] As used herein, an "intelligent prosthesis" or "intelligent medical device" is preferably an implantable or implanted medical device that replaces or functionally complements a patient's native body part. As used herein, the term "intelligent prosthesis" is used interchangeably with "intelligent implant", "smart implant", "smart medical device", "joint implant", "implanted medical device", or another similar term. When an intelligent prosthesis performs kinematic measurements, it may be referred to as a "kinematic medical device", or a "kinematic implantable device". In describing embodiments of the present invention, reference may be made to a kinematic implantable device, but it should be understood that this is merely an example of an intelligent medical device that can be employed in the apparatus, methods, systems, etc. of the present invention. Whether or not an intelligent prosthesis attempts to perform kinematic measurements, or attempts to perform other or additional measurements, the prosthesis will have or be associated with an implantable report processor (IRP). In one embodiment, an intelligent prosthesis is an implanted or implantable medical device comprising an implantable report processor configured to perform the functions as described herein.An intelligent prosthesis can perform one or more of the following exemplary operations to characterize the implanted state of the intelligent prosthesis. These exemplary operations include identifying the intelligent prosthesis or a part thereof by recognizing one or more unique identification codes related to the intelligent prosthesis or a part thereof, detecting, sensing and / or measuring parameters, which may be referred to as monitoring parameters, for collecting operation data, kinematic data, or other data related to the intelligent prosthesis or a part thereof (such data may optionally be collected as a function of time), storing the collected data within the intelligent prosthesis or a part thereof, and transmitting the collected data and / or the stored data from the intelligent prosthesis or a part thereof to an external computing device by means of a wire harness. The external computing device may have at least one data storage location, such as a personal computer, a base station, a computer network, a cloud-based storage system, or another computing device with access to such a storage system, or may have access to such at least one data storage location in a different way. A non-limiting and non-exhaustive list of embodiments of intelligent prostheses includes arthroplasty, such as total knee arthroplasty (TKA), TKA tibial plate, TKA femoral component, TKA patellar component, tibial extension, total hip arthroplasty (THA), femoral component for THA, acetabular component for THA, shoulder arthroplasty, breast implant, intramedullary rod for repairing arm or leg fractures, lateral bending rod, dynamic hip screw, spinal intervertebral spacer, spinal artificial disc, annuloplasty ring, heart valve, intravascular stent, vascular graft and vascular stent graft.

[0027] As used herein, "kinematic data" includes, individually or collectively, some or all of the data that is associated with a particular kinematic implantable device and available for communication with the outside of the particular kinematic implantable device. For example, kinematic data can include raw data from one or more sensors of a kinematic implantable device, where the one or more sensors include, for example, gyroscopes, accelerometers, pedometers, strain gauges, etc., that generate data related to motion, force, tension, velocity, or other mechanical forces. Kinematic data can also include processed data, status data, operation data, control data, fault data, time data, schedule setting data, event data, log data, etc., from one or more sensors associated with a particular kinematic implantable device. In some cases, high-resolution kinematic data includes kinematic data from one, many, or all of the sensors of a kinematic implantable device, and such kinematic data is collected from many sensors with high quality, high resolution, frequently, and so on.

[0028] In one embodiment, the term kinematic means the measurement of the angles, velocities, and accelerations of body segments (body segments) and joints during movement. A body segment is considered a rigid body for the purpose of explaining body movement. Examples of body segments include the foot, tibia (leg), thigh, pelvis, thorax, hand, forearm, upper arm, and head. Examples of joints between adjacent body segments include the ankle joint (the joint combining the talocrural joint and the subtalar joint), the knee joint, the hip joint, the wrist joint, the elbow joint, and the shoulder joint. Position describes the location of a body segment or joint in space measured, for example, in meters in terms of distance. A related measurement called displacement represents the position relative to the starting position. In two dimensions, the position is given in a Cartesian coordinate system, that is, first the horizontal position and then the vertical position. In one embodiment, a kinematic implant or an intelligent kinematic implant obtains kinematic data and, optionally, obtains only kinematic data.

[0029] "Sensor" means a device that can be used to perform one or more of detection, measurement, and / or monitoring from one or more different perspectives of body tissue (anatomical perspective, physiological perspective, metabolic perspective, and / or functional perspective) and / or from the perspective of an orthopedic device or implant. Representative examples of sensors suitable for use in the present invention include, for example, fluid pressure sensors, fluid volume sensors, contact sensors, position sensors, pulse pressure sensors, blood volume sensors, blood flow sensors, chemical sensors (e.g., for blood and / or other body fluids), metabolic sensors (e.g., for blood and / or other body fluids), accelerometers, mechanical stress sensors, and temperature sensors. In certain embodiments, the sensor may be a wireless sensor, and in other embodiments, it may be a sensor connected to a wireless microprocessor. In another embodiment, one or more (including all) of the sensors may preferably have a unique sensor identification number ("USI") that identifies the sensor. In certain embodiments, the sensor is a device that can be used to quantitatively measure one or more different perspectives of body tissue (anatomical perspective, physiological perspective, metabolic perspective, and / or functional perspective) and / or one or more perspectives of an orthopedic device or implant. In certain embodiments, the sensor is an accelerometer that can be used to quantitatively measure one or more different perspectives of body tissue (e.g., functional perspective) and / or one or more perspectives of an orthopedic device or implant (e.g., alignment within a patient).

[0030] A variety of sensors (Micro (micro) Electro-Mechanical Systems, i.e., "MEMS", or Nano-Electro-Mechanical Systems, i.e., "NEMS", and BioMEMS or BioNEMS, for which, generally, see https: / / en.wikipedia.org / wiki / MEMS) can be used in the present invention. Representative patent documents include U.S. Patent No. 7,383,071, No. 7,450,332, No. 7,463,997, No. 7,924,267, No. 8,634,928, and U.S. Patent Application Publication Nos. 2010 / 0285082 and 2013 / 0215979. Substitute publications (non-patent documents) include Albert Foch, "Introduction to BioMEMS", CRC Press, 2013; Marc J. Madou, "From MEMS to Bio-MEMS and Bio-NEMS: Manufacturing Techniques and Applications", CRC Press, 2011; Simona Badilescu, "Bio-MEMS: Science and Engineering Perspectives", CRC Press, 2011; Steven S.Saliterman), "Fundamentals of BioMEMS and Medical Microdevices", SPIE - The International Society of Optical Engineering, 2006, edited by Wanjun Wang and Steven A. Soper, "Bio - MEMS: Technologies and Applications", CRC Press, 2012, Volker Kempe, "Inertial MEMS: Principles and Practice", Cambridge University Press, 2011, Polla, D. L. et al., "Microdevices in Medicine", Ann. Rev. Biomed. Eng., 2000, Vol. 2, pp. 551 - 576, Yun, K. S. et al., "A Surface - Tension Driven Micropump for Low - voltage and Low - Power Operations", J. Microelectromechanical Sys., October 2002, 11:5, pp. 454 - 461, Yeh, R. et al.), "Single Mask, Large Force, and Large Displacement Electrostatic Linear Inchworm Motors", Journal of Microelectromechanical Systems (J. Microelectromechanical Sys.), August 2002, 11:4, pp. 330-336, Loh, N. C. et al., "Sub-10 cm3 Interferometric Accelerometer with Nano-g Resolution", Journal of Microelectromechanical Systems (J. Microelectromechanical Sys.), June 2002, 11:3, pp. 182-187 are cited, and all of the above non-patent documents are incorporated herein by reference in their entirety, and the entire contents of these descriptions are made a part of this specification.

[0031] To better understand the various aspects of the embodiments of the invention provided herein, the following sections are provided: A. Intelligent medical devices and implants, B. Systems including intelligent implants, C. Joint implants and systems including joint implants, D. Computer systems for analysis, dissemination of information, ordering, and supply: processing of IMU data recorded during patient monitoring, E. Methods and devices for stabilizing artificial joints, F. Methods and devices for adjusting the position of artificial joints, G. Joint inserts and their use, and H. Clinical solutions and outcomes.

[0032] A. Intelligent Medical Devices and Implants In one aspect, the present invention provides a medical device including a medical device (implant) implantable in a patient's body, and such medical device is available for monitoring and recording the state and / or activity of the medical device, and the state and / or activity include postoperative activities and the course of the patient, as well as these characteristics. In one embodiment, the present invention achieves the benefits of a medical implant, such as those provided by a prosthesis, replacing or complementing the patient's native functions, while also achieving the benefits of monitoring and reporting that provide insights into the functions and / or states of the instrument and / or the patient who has received and accepted the implanted instrument. In one embodiment, the medical device is an implantable device implanted in a living host (also called a patient) to improve or replace the biological structure or organ function of the patient's body, such as an implantable prosthesis.

[0033] In one embodiment of the present invention, the medical implant is a stent graft, and the intelligent implant is, for example, a stent graft coupled to a sensor as disclosed in WO 2014 / 100795 pamphlet and US Patent No. 9,949,692, and WO 2016 / 044651 pamphlet and US Patent Application Publication No. 2016 / 0310077.

[0034] In one embodiment of the present invention, the medical implant is a stent, and the intelligent implant is a stent coupled to a sensor, such as a stent monitoring assembly disclosed in WO 2014 / 144070 pamphlet and US Patent Application Publication No. 2016 / 0038087, and WO 2016 / 044651 pamphlet and US Patent Application Publication No. 2016 / 0310077.

[0035] In one embodiment of the present invention, the medical implant is a hip joint replacement prosthesis including one or more of a femoral shaft, a femoral head, and an acetabular implant, and the intelligent implant is a hip joint replacement prosthesis or a component thereof, for example, a sensor coupled to the hip joint replacement prosthesis disclosed in WO 2014 / 144107 pamphlet and US Patent Application Publication No. 2016 / 0029952, and WO 2016 / 044651 pamphlet and US Patent Application Publication No. 2016 / 0310077.

[0036] In one embodiment of the present invention, the medical implant is a medical tube, and the intelligent implant is a medical tube coupled to a sensor. The medical tube refers to a generally cylindrical body that can be used in medical procedures (e.g., the tube is generally sterile, non-pyrogenic, and / or suitable for use in the human body and / or suitable for implantation into the human body). For example, the tube can be used to 1) bypass an obstacle (e.g., in the case of a coronary artery bypass graft, i.e., "CABG" and a peripheral vascular bypass graft) or cut through an obstacle (e.g., a balloon dilation catheter, an arterial angioplasty balloon), 2) release pressure (e.g., a shunt, a drainage tube and a drainage catheter, a urinary catheter), 3) restore or support an anatomical structure (e.g., an endotracheal tube, a tracheostomy tube, and a feeding tube), 4) provide access (e.g., a CVC catheter, a peritoneal catheter and a hemodialysis catheter). Representative examples of tubes include catheters, eustachian tubes, drainage tubes, tracheostomy tubes (e.g., Durham fermentation tubes), bronchial intubation tubes, endotracheal tubes, esophageal tubes, feeding tubes (e.g., nasogastric tubes or NG tubes), gastric tubes, rectal tubes, colonic tubes, and various grafts (e.g., bypass grafts). For example, for the disclosure of medical tubes and sensors attached thereto, reference may be made to WO 2015 / 200718 pamphlet and US 2017 / 0196478 specification, and WO 2016 / 044651 pamphlet and US 2016 / 0310077 specification. In one embodiment, the medical tube is selected from a catheter, an eustachian tube, a drainage tube, a tracheostomy tube, a bronchial intubation tube, an endotracheal tube, an esophageal tube, a feeding tube, a gastric tube, a rectal tube, and a colonic tube.

[0037] In one embodiment of the present invention, the medical implant is an aesthetic (cosmetic) implant, and the intelligent implant is an aesthetic or cosmetic implant coupled to a sensor. The cosmetic implant refers to an artificial or synthetic prosthesis implanted in or implantable in the body. Implants are typically utilized to strengthen or replace body structures, and such implants are used in a wide variety of cosmetic applications, such as, for example, facial implants (e.g., lip, jaw, nose, nasolabial fold, and cheekbone implants), penile implants, and body contour implants (e.g., breast, pectoral muscle, calf, buttock, abdominal, and biceps / triceps). For example, for the disclosure of cosmetic implants and sensors attached thereto, refer to WO 2015 / 200704 pamphlet and US Patent Application Publication No. 2017 / 0181825, as well as WO 2016 / 044651 pamphlet and US Patent Application Publication No. 2016 / 0310077. In one embodiment, the cosmetic implant is a breast implant.

[0038] In one embodiment of the present invention, the medical implant is a spinal implant, and the intelligent implant is a spinal implant coupled to a sensor. Examples of spinal devices and implants include pedicle screws, spinal rods, spinal wires, spinal plates, spinal cages, artificial intervertebral discs, bone cements, and combinations thereof (e.g., one or more pedicle screws and a spinal rod, one or more pedicle screws and a spinal plate). Additionally, a medical delivery device that disposes a spinal device and implant together with one or more sensors can also be said to be an intelligent medical device according to the present invention. Examples of medical delivery devices for spinal implants include percutaneous posterior correction balloons, catheters (thermal catheters and bone tunnel catheters), bone cement injection devices, microscopic discectomy tools, and other surgical tools. For example, for the disclosure of a spinal implant and a sensor attached thereto, and a sensor-equipped delivery device for disposing a spinal device, refer to International Publication No. WO 2015 / 200720 pamphlet and U.S. Patent Application Publication No. US 2017 / 0196508 specification, and International Publication No. WO 2016 / 044651 pamphlet and U.S. Patent Application Publication No. US 2016 / 0310077 specification. Note that any of these spinal implants, sensors, and delivery devices may be the intelligent medical device or intelligent implant of the present invention.

[0039] In one embodiment of the present invention, the medical device may be a part of orthopedic hardware that may or may not be implantable, and the intelligent medical device is a sensor coupled to a part of orthopedic hardware that may or may not be implantable orthopedic hardware. Examples of orthopedic instruments and implants include external hardware (e.g., casts, braces, external fixators, tension bandages, slings, and supports) and internal hardware (e.g., K-wires, pins, screws, plates, and intramedullary devices (e.g., rods and nails)). Additionally, a medical carrier for placing one or more orthopedic instruments and implants together with one or more sensors may also be an intelligent medical device of the present invention. Examples of medical carriers for orthopedic hardware include drills, drill guides, mallets, guide wires, catheters, bone tunneling catheters, microsurgical tools, and general surgical tools. For example, for the disclosure of orthopedic hardware and sensors attached thereto, and sensor-equipped carriers for placing orthopedic hardware, refer to International Publication No. WO 2015 / 200722 pamphlet and U.S. Patent Application Publication No. US 2017 / 0196499 specification, and International Publication No. WO 2016 / 044651 pamphlet and U.S. Patent Application Publication No. US 2016 / 0310077 specification. Note that all of the sensor-equipped orthopedic hardware and sensor-equipped carriers may be intelligent medical devices and intelligent implants of the present invention.

[0040] In one embodiment of the present invention, the medical device is a medical polymer used in medical procedures. A variety of polymers can be used as medical polymers, in which case the attached sensor can monitor the integrity and effectiveness of the polymer (whether used alone or as part of another medical device or implant, or whether attached to another medical device or implant). The medical polymers of the present invention can be formed into a wide variety of shapes and dimensions suitable for medical applications. Representative examples of polymer forms include solid forms, such as films, sheets, shaped articles, cast articles, or cut articles. Other solid forms include extruded forms that can be made in the form of tubes (e.g., shunts, drainage tubes, and catheters) and fibers that can be braided into a mesh or used to make sutures. Liquid forms of the polymer include gels, dispersions, colloidal suspensions, and the like. Particularly preferred polymers used in the present invention can be provided in a sterilized and / or non-pyrogenic form and are medical polymers suitable for use in the human body. Representative examples of polymers include polyester, polyurethane, silicone, epoxy resin, melamine formaldehyde resin, acetal, polyethylene terephthalate, polysulfone, polystyrene, polyvinyl chloride, polyamide, polyolefin, polycarbonate, polyethylene, polyamide, polyimide, polypropylene, polytetrafluoroethylene, ethylene propylene diene rubber, styrene (e.g., styrene butadiene rubber), nitrile (e.g., nitrile rubber), hypalon, polysulfide, butyl rubber, silicone rubber, cellulose, chitosan, fibrinogen, collagen, hyaluronic acid, PEEK, PTFE, PLA, PLGA, PCL, and PMMA. For example, for the disclosure of polymers and sensors attached thereto, reference may be made to WO 2015 / 200723 pamphlet and US Patent Application Publication No. 2017 / 0189553, as well as WO 2016 / 044651 pamphlet and US Patent Application Publication No. 2016 / 0310077.Note that all of the polymer and the sensors attached thereto may preferably be the intelligent medical devices and intelligent implants of the present invention.

[0041] In one embodiment of the present invention, the medical device is a heart valve, and the intelligent medical device is a heart valve coupled to a sensor. A "heart valve" is an instrument that can be implanted into the heart of a patient with vascular disease. There are three main types of heart valves, namely, mechanical valves, biological valves, and tissue engineering valves (however, for the purposes of the present invention, tissue engineering valves are considered together with other biological valves). Mechanical valves typically fall into two categories: 1) heart valves for surgical procedures using a sternotomy or "open heart" technique (e.g., "caged ball type", "tilting disc type", mitral and tricuspid designs), and 2) transcutaneously implantable heart valves that can often include valve leaflets made from biological sources (bovine or porcine pericardium) (e.g., stent-frame attached (self-expanding stent or balloon-expandable stent) or non-stent-frame design). Tissue-based or "biological" valves are typically made from porcine or bovine sources and are typically prepared from either an animal valve (e.g., a porcine valve) or tissue of a pericardial sac (e.g., a bovine pericardial valve or a porcine pericardial valve). Tissue engineering valves are valves artificially created on a "scaffold" (e.g., by the growth of appropriate cells on a tissue scaffold). Tissue engineering valves have not yet been commercially adopted. For example, for the disclosure of a heart valve and a sensor attached to the heart valve, which may preferably be the medical device and the intelligent medical device of the present invention, respectively, see International Publication No. WO 2015 / 200707 pamphlet and U.S. Patent Application Publication No. US 2017 / 0196509 specification, and International Publication No. WO 2016 / 044651 pamphlet and U.S. Patent Application Publication No. US 2016 / 0310077 specification. In various embodiments, the heart valve is a mechanical heart valve, such as a caged ball design, a tilting disc mechanical valve, a mitral or tricuspid mechanical valve, a self-expanding percutaneous heart valve, a percutaneous heart valve, or a balloon-expandable percutaneous artificial heart valve. The medical device equipped with a sensor may preferably be a balloon delivery device for a balloon-expandable percutaneous heart valve.

[0042] In one embodiment, the medical implant replaces a patient's joint, such as the knee joint, shoulder joint, or hip joint, and with such medical implant, the patient can have the same or substantially the same mobility as provided by a healthy joint. When the medical implant replaces a joint, in one embodiment, a sensor coupled to the implant can monitor displacement or movement. Generally, there are three forms of three-dimensional motion that a sensor can detect within and around the joint, namely, core walking (or limb mobility in the case of shoulder or elbow arthroplasty), macroscopic instability, and microscopic instability. These motions will be described in the context of a TKA implant, but such motions are also applicable to hip arthroplasty, shoulder arthroplasty, elbow arthroplasty, and ankle arthroplasty. For example, for the disclosure of the medical implant and its intelligent version that can replace a patient's joint and be used in the present invention, reference may be made to International Publication Pamphlets No. WO 2014 / 144107, No. WO 2014 / 209916, No. WO 2016 / 044651, and No. WO 2017 / 165717.

[0043] In one embodiment, the medical implant is a knee joint implant, and in particular, an artificial knee joint implant for total knee arthroplasty. The sensor attached to the artificial knee joint implant of the present invention can monitor and characterize the movement of the knee joint implant, where this movement can take the form of, for example, core walking, macroscopic instability, and microscopic instability as described below.

[0044] FIG. 1 is a perspective view of an exemplary embodiment of a report processor 10 that can be used to utilize the exemplary intelligent implant described in the exemplary embodiment shown in FIG. 2. In the embodiment shown in FIG. 1, the implantable report processor 10 includes an outer casing 12 that surrounds a power component (battery) 14, an electronics assembly 16, and an antenna 20. One component of the casing is a radome 18 that is used to cover and protect the antenna, and with this antenna, the implantable report processor can receive and send information. The outer casing 12 may have a set screw engagement hole 22 that can be used to physically attach the report processor 10 to the tibial plate 32 as shown in FIG. 2.

[0045] FIG. 2 is a perspective view of a tibial component 30 that can be used to embody an exemplary embodiment of the present invention. For example, the tibial component 30 shown in FIG. 2 may have an implantable medical device for TKA, such as a tibial extension. Referring to the exemplary embodiment shown in FIG. 2, the tibial component 30 includes a tibial plate 32 physically attached to the upper surface of the tibia 34. For example, the tibial plate 32 may be a base plate section of an artificial knee joint (prosthesis) that can be implanted during a surgical procedure, such as TKA. Prior to or during the surgical procedure, the implantable report processor 10 of FIG. 1 may be physically attached to the tibial plate 32 and implanted into the tibia 34. Regarding the exemplary embodiment shown in FIG. 2, the tibial component 30 includes the tibial plate 32 and the report processor 10, which are surgically implanted to form a tibial extension 36.

[0046] Core walking is described as the movement associated with basic locomotion. Core walking occurs mainly in the sagittal plane, and its frequency range is 0.5 Hz to 5 Hz. Most commonly, this can be considered as a basic walking motion that starts with the toes leaving the ground, swings forward with the knee bent in combination with the movement of the hip joint, extends when the heel strikes the ground, and then rotates the foot back to the position where the toes leave the ground.

[0047] Macrostability is a partial collection of the movements of core walking and is related to musculoskeletal instability when loading the joints during the walking process. As an example, simply put, this can be considered as uncontrolled medial-lateral and / or anterior-posterior movements when rising from a chair or going up and down stairs, with its frequency range in the range of 2 Hz to 20 Hz and its movement range from 5 mm to 10 cm.

[0048] Microinstability is another partial collection of motions associated with motion within the TKA joint resulting from malalignment between the femoral component, tibial plate, and its tibial insert. This motion may occur in the anterior-posterior plane and / or the medial-lateral plane, with a frequency range from 5 Hz to 50 Hz, and a motion range from 0.1 mm to 2 cm in any combination or one combination of these directions. This motion may be due to improper sizing of the implant at the time of the initial procedure, changes in the musculoskeletal structure associated with weight loss and / or another trauma, and / or joint wear resulting in changes in the polymer pack geometry and fit with the femoral component. Additionally, this motion may be caused by loosening of the tibial component itself due to bone loss associated with osteoporosis and / or other metabolic disorders affecting poor bone structure or bone density. It goes without saying that the above microinstability may be due to a combination of the above-described motion modalities. Both macroinstability and microinstability may be associated with pain and a decrease in the metric of quality of life for the patient.

[0049] Sensor modalities implanted into the bone and integrated with the TKA or sensors actually implanted only into the bone and not necessarily bonded to the implant address signal fidelity and compliance constraints of external devices. However, there remains a need to identify sensor data signatures that represent instability with sufficient fidelity to enable an "early warning system" prior to bone erosion, degradation of the TKA hardware, and the onset of pain, without the need for invasive / expensive interventions. The present invention addresses this need.

[0050] In various embodiments, the present invention provides methods and devices that include implanted sensors coupled to TKA hardware and / or coupled to bone, where the sensors have sufficient sensitivity and specificity to detect movement of the tibia (or the tibial component of a TKI) that is consistent with the identification of an instability signature. An "instability signature" is defined as having a characteristic frequency response of about 20 Hz or greater, about 25 Hz or greater, or about 30 Hz or greater, and about 90 Hz or less, about 100 Hz or less, or about 110 Hz or less, and this instability signature indicates that the TKA hardware is not firmly engaged with the tibia. Normal kinematic movements during normal human movement are typically about 20 Hz or less, and device movements associated with wear, abrasion, and lack of osseointegration (collectively referred to as degradation) are typically associated with movements of 100 Hz or greater. Device instability typically results in movements of about 20 Hz to about 100 Hz. The present invention provides a sensor coupled to the intelligent implant of the present invention, and this sensor has a dynamic range sufficient to detect and distinguish between i) normal kinematic movements (typically about 20 Hz or less), ii) implant instability (typically about 20 - 100 Hz), and iii) implant degradation or lack of osseointegration (typically about 100 Hz or greater). The sensor preferably has a dynamic range high enough to avoid being saturated by normal kinematic movements but sensitive enough to detect the slight movements / impacts that represent the "instability signature". Additionally, the sensor preferably has a frequency response and sample rate sufficient to identify, without aliasing, i) normal kinematic movements, ii) the instability signature, and iii) the degradation signature.

[0051] In various embodiments, the present invention provides a medical device coupled to an execution motion sensor (e.g., one or more of sensors selected from an accelerometer detecting acceleration and a gyroscope), and provides an algorithm capable of quantifying the degree of instability, i.e., a movement of 2 mm for a movement of 1 mm or a movement of 10° for a movement of 5°, where the degree of instability is determined from a defined transient signature conforming to definitions regarding time and spectrum. From this information, the degree of instability can be evaluated over time, and the "intervention threshold" can be determined based on i) clinical data, ii) anatomical thresholds, iii) design constraints and analysis of the TKA device, and other factors.

[0052] In one aspect, the present invention provides a report processor adapted to be implanted with a medical device, e.g., a prosthesis, where the report processor typically monitors the state of the device after implantation by obtaining kinematic data in the range from about 10 Hz to 120 Hz. This report processor is also referred to as an implantable report processor, or IRP. As described herein, the state of the device may include the integrity of the device, the movement of the device, the forces exerted on the device, and other information regarding the implanted device. The present invention also provides a medical device having a structure that can easily accommodate the IRP. An implantable medical device with an IRP is also referred to as an intelligent implant, in that the implant recognizes that it is monitoring its own state or condition and thereby obtaining data, where the data is stored within the implant and can then be transmitted to a separate device for review, e.g., by a physician, as needed.

[0053] For example, an intelligent implantable device of the present invention with suitable internal electronic components may monitor and measure the movement of a synthetic joint (prosthesis) of a patient undergoing surgery implanted by total knee arthroplasty (TKA), store measurement data and unique identification information of the prosthesis components, and use this data to transmit to external beneficiaries (e.g., physicians, clinicians, medical assistants, etc.) as needed. The IRP includes one or more sensors, such as gyroscopes, accelerometers, and temperature and pressure sensors, which can be placed somewhere within the outer casing of the IRP. For example, all of these sensors can be placed on a printed circuit board. In one embodiment, for example, when the intelligent implant is an artificial joint, the IRP performs kinematic measurements. In another embodiment, the IRP only performs kinematic measurements. Thus, the intelligent joint implant may preferably have sensors for kinematic measurements to determine the movement received by the implanted prosthesis.

[0054] The intelligent medical device of the present invention may preferably have components for total or partial joint replacement surgery, and this total or partial joint replacement surgery may occur during the performance of total knee arthroplasty (TKA) where, for example, the IRP may be or be attached to a tibial component, a femoral component, and / or a component of the tibial extension, or during the performance of hip replacement surgery where, for example, the IRP may be or be attached to a femoral component for hip replacement surgery or a component of the acetabular component, or during the performance of shoulder replacement surgery where, for example, the IRP may be or be attached to a component of the humeral component for shoulder replacement surgery. Other examples of medical devices that can be combined with the IRP to provide an intelligent implant include breast implants, lumbar vertebral cages, artificial spinal discs, dynamic hip screws, and intramedullary rods for the leg.

[0055] The IRP and the medical device are each adapted to be implanted into a living subject, such as a mammal, such as a human, a horse, a dog, etc. Thus, in one embodiment, the IRP is sterile, e.g., treated with sterilizing radiation or ethylene oxide. In another embodiment, the intelligent implant having the IRP and the medical device is, in two examples, also optionally sterile by being treated with sterilizing radiation or ethylene oxide. To be protected from the in-vivo environment, in one embodiment, the IRP is hermetically sealed so that body fluids cannot enter the IRP. The subject into which the medical device is implanted may be referred to herein as a patient as another expression. In one embodiment, the subject / patient is a human.

[0056] An implantable device needs to be robust for placing such a device and small or space-efficient because the space within the body and / or the artificial implant is limited. The challenge to the commercial success of an implantable device with internal electronic components and an internal or external transmission antenna is that the device and / or the transmission antenna must not be inappropriately large, their power consumption must be such that they can operate over a moderately long period (i.e., not over a limited duration), and they should be made such that they are not adversely affected by their local biological environment. The IRP of the present invention preferably has a suitable antenna that is space-efficient internally or externally and / or power-efficient.

[0057] An intelligent implant has, as an option, a power source required to operate electronics within the IRP that measures, records, and sends data regarding the state of the implant. Some medical implants already have a power source. An example of an implantable prosthesis that can improve the function of an organ and has a power source is an implantable atrial defibrillator, which detects when the heart has entered an abnormal rhythm known as "atrial fibrillation" and generates one or more electrical pulses to restore the heart to normal sinus rhythm. Typically, this power source is in the form of a battery.

[0058] Because the charge of the battery may be relatively short-lived, the prosthesis is typically placed in a practical body region for replacing the battery or removing the prosthesis to charge the battery. For example, an atrial defibrillator is typically implanted just beneath the skin of the patient's chest. For battery replacement, a surgeon makes an incision, removes the old defibrillator, implants a new defibrillator with a new battery, and closes the incision. Alternatively, the patient or a physician, such as a cardiologist, can recharge the battery by placing a device on the implanted defibrillator that inductively couples (sometimes called magnetically couples) to recharge the battery without removing the defibrillator from the subject.

[0059] Unfortunately, removing the prosthesis to replace the battery is often undesirable because it is relatively expensive for at least that purpose and requires invasive procedures that can cause side effects such as infection and abrasions. Charging an implanted battery by electromagnetic induction is non-invasive, but it is impractical or impossible to position the prosthesis so that the battery can be charged by electromagnetic induction. In addition, the size of the coil required to transmit power is large relative to the device, which can pose problems with respect to the limited space available within the body. The time required for charging can be excessive, and if the coil alignment is lost, excessive heat can be generated, potentially damaging the surrounding tissue. Moreover, the inductive battery form can render the implant incompatible with MRI use. In addition, the chemistry of the battery that is compatible with charging (i.e., a secondary battery) generally has a significantly lower energy storage capacity compared to a battery of approximately the same size constructed using a non-rechargeable chemistry (i.e., a primary battery).

[0060] A variant that can solve the latter problem is to implant the battery at a location remote from the prosthesis in which the battery is implanted in a practical location for electromagnetic induction charging of the battery. The advantage of implanting at a location remote from the prosthesis in which the battery is implanted is that the battery can be made larger and thus last longer than when it is placed within the prosthesis. However, implanting the battery remotely from the prosthesis in which the battery is implanted may give rise to several drawbacks. For example, even if the battery is appropriately positioned for inductive charging, the charging device may be too expensive or complex for home use, the patient may forget to charge the device, and visiting the doctor regularly to charge the battery can be inconvenient and costly for the patient. Further, it may be difficult to implant the wires used to couple the battery to a remotely (from the battery) implanted prosthesis, or, when wirelessly powering an implant sensor from a rechargeable battery, the sensor may have limited measurement capabilities. Further, since the battery is generally implanted just beneath the skin to increase the inductive coupling coefficient, the battery may be visible and embarrassing to the patient, and moreover the battery may physically discomfort the patient.

[0061] Thus, an implantable reporting process (IRP) may have a power source (e.g., a battery) and a mechanism for managing the power output of the implanted power source, and thus the power source is adapted to provide power over a sufficient period regardless of the location of the power source within the patient's body. The IRP can accommodate only the power source present within the intelligent implant.

[0062] An example of a battery suitable for use in an implantable report processor includes a container sized to fit inside the bone of a living patient, and this battery has a lifespan sufficient to power the electronic circuits within the implantable report processor for a period suitable for the prosthesis in which the implantable report processor is housed, for example, a lifespan of several years. The battery may be configured to be placed directly in the bone or may be configured to be placed within a portion of the implantable report processor placed in the bone. Alternatively, the battery may be configured to be placed within a non-bony area of the living body that is impractical to charge and impractical to replace prior to replacement of the prosthesis or other device associated with the battery.

[0063] An IRP typically has an outer casing that houses a plurality of components. Suitable exemplary IRP components include a signal portal, an electronics assembly, and a power source. In one embodiment, the IRP has each of a signal portal, an electronics assembly, and a power source. The signal portal functions to receive and transmit wireless signals, and such a signal portal may, for example, have an antenna for transmitting wireless signals. The electronics assembly includes a circuit assembly, which may include, for example, a printed circuit board and electrical components that may be formed on one or more integrated circuits (ICs) or chips. The chips may be, for example, a wireless transmitter chip, a real-time clock chip, one or more sensor components such as an inertial measurement unit (IMU) chip, a temperature sensor, a pressure sensor, a pedometer, a memory chip, etc. Additionally, the electronics assembly may include a header assembly that serves as a communication interface between the circuit assembly and the signal portal (e.g., the antenna). The power source provides the energy necessary to operate the IRP, and this power source may be, for example, a battery. The IRP further includes one or more sensors such as a gyroscope, an accelerometer, a pedometer, a temperature sensor, and a pressure sensor, and these sensors can be arranged anywhere within the IRP outer casing. For example, all of these sensors may be arranged on the printed circuit board. More precisely, embodiments of the present invention relate to a space-efficient printed circuit assembly (PCA) for an implantable report processor (IRP). The implantable report processor may further have a plurality of transmission antennas structured in various forms. Accordingly, embodiments of the present invention relate to a plurality of improved space-efficient and power-efficient antennas configured for an implantable report processor, such as an IRP.

[0064] An example of an implantable report processor has an outer casing or housing dimensioned to fit into or form part of a prosthesis having at least a portion designed to fit within the bone of a living patient. An electronic circuit is disposed within the housing and is configured to provide information related to the prosthesis to a destination located outside the patient's body. A battery is also provided within the housing and is coupled to the electronic circuit.

[0065] An example of a prosthesis has a receptacle for receiving an implantable report processor that is preferably designed to fit into a cavity formed within the bone of a living patient. For example, the implantable report processor may be provided within or form part of a tibial component or tibial extension of an artificial knee joint, and the tibial component or tibial extension is designed to fit into a cavity formed within the tibia of a living patient.

[0066] The power profile of the electronic circuit of the implantable report processor may be configured such that the battery has a desired expected life suitable for the form of the prosthesis (or other device) associated with the battery. For example, such a desired expected life may range from 1 year to 15 years or more, such as 10 years. One embodiment of such a circuit has a supply node configured to be coupled to the battery, at least one peripheral circuit, a processing circuit coupled to the supply node and configured to couple at least one peripheral circuit to the supply node, and a timing circuit coupled to the supply node and configured to activate the processing circuit at a set time or at a plurality of set times.

[0067] The base station may be provided to facilitate communication of the implantable report processor before and after the implantable report processor is implanted into the patient's body as part of a prosthesis, and also to act as an interface between the report processor and another computing system, such as a database or remote server on the "cloud". The base stations can take different forms. For example, the base station may be configured to be usable by a surgeon or other specialist before the prosthesis is implanted. The base station may also be configured to be usable within the patient's residence. For example, the base station may be configured to periodically and automatically poll the implantable report processor (e.g., while the patient is sleeping) so that information obtained or generated by the processor regarding the prosthesis can be obtained, and to provide this information to another computing system for storage or analysis by means of a wireless Internet connection. And the base station may be configured to be usable within a doctor's clinic while the doctor is checking the operation and function of the prosthesis and the patient's health related to the prosthesis. Further, the network of which the base station is a part may include a voice command device (e.g., Amazon Echo®, Amazon Dot®, Google Home®) configured to interact with the base station.

[0068] For example, for the disclosure of a medical device with a sensor that can be used as an intelligent implant of the present invention complementarily as described herein as an option, refer to U.S. Patent Application Publication No. 2016 / 0310077 (Title of the Invention: Devices, Systems and Methods for Using and Monitoring Medical Devices). This U.S. Patent Application Publication is hereby incorporated by reference in its entirety and made a part of this specification. Also, for example, for the disclosure of a medical device with a sensor that can be used as an intelligent implant of the present invention in a complemented state as described herein as an option, refer to International Publication Pamphlet No. 2017 / 165717 (Title of the Invention: Implantable Reporting Processor for an Intelligent Implant). This international publication is hereby incorporated by reference in its entirety and made a part of this specification.

[0069] B. Systems Including Intelligent Implants An intelligent implant is preferably one component of a system of the present invention, including one or more of: 1) a sensor that detects and / or measures the performance state of the implant and / or the environment immediately around the implant and / or the patient's activity level; 2) a memory that stores data from the detection and / or measurement results; 3) an antenna that transmits the data; 4) a base station that can receive the data generated by the sensor and transmit this data and / or the analyzed data to a cloud-based location; 5) a cloud-based location that can store and analyze the data, store the analyzed data, and / or further analyze it; 6) a receiving terminal that receives the output from the cloud-based location. The receiving terminal can be accessed, for example, by a healthcare professional or an insurance company or the manufacturer of the implant. The output can determine the state of the implant and / or the performance state of the implant and / or the state of the patient who received the implant, and can provide a recommended example for dealing with any concerns that may have arisen from the analysis of the original data.

[0070] The system of the present invention may be described as a kinematic implantable device as an intelligent implant, as provided in the following paragraphs. However, these systems are applicable to any intelligent medical device including the intelligent medical devices described herein. For example, for the disclosure of the system according to the present invention complemented as described herein as an option, refer to U.S. Patent Application Publication No. 2016 / 0310077 (Title of the Invention: Devices, Systems and Methods for Using and Monitoring Medical Devices). This U.S. Patent Application Publication is hereby incorporated by reference in its entirety and made a part of this specification. Also, for example, for the disclosure of the system according to the present invention complemented as described herein as an option, refer to International Publication Pamphlet No. 2017 / 165717 (Title of the Invention: Implantable Reporting Processor for an Intelligent Implant). This international publication is hereby incorporated by reference in its entirety and made a part of this specification.

[0071] C. Joint Implants and Systems Including Joint Implants FIG. 3 is a diagram showing the situation of an environment 1000 of a kinematic implantable device. In this environment, a kinematic implantable device 1002 is implanted into a patient (not shown in FIG. 3) by a medical staff (not shown in FIG. 3). The kinematic implantable device 1002 is configured to collect data including the operation data of the device 1002 together with kinematic data related to a specific movement of the patient or a specific movement of a part of the patient's body, for example, one of the patient's knee joints. The kinematic implantable device 1002 communicates with one or more base stations or one or more smart devices during various monitoring stages of the patient.

[0072] For example, in connection with a medical procedure, the kinematic implantable device 1002 is implanted within a patient's body. Concurrent with the medical procedure, the kinematic implantable device 1002 communicates with an operating room base station (not shown in FIG. 3). Subsequently, after sufficient recovery from the medical procedure, the patient returns home, in which case the kinematic implantable device 1002 is configured to communicate with a home base station 1004. Ordinarily, the kinematic implantable device 1002 is configured to communicate with a base station at a physician's clinic (not shown in FIG. 3). The kinematic implantable device 1002 communicates with each base station via a short-range network protocol, such as Medical Implant Communication Service (MICS), Medical Device Wireless Communication Service (MedRadio), or some other wireless communication protocol suitable for use in conjunction with the kinematic implantable device 1002.

[0073] The kinematic implantable device 1002 is implanted within a patient's body (not shown in FIG. 3). The kinematic implantable device 1002 may be a stand-alone medical device or, alternatively, a component within a larger medical device, such as an artificial joint (e.g., a replacement knee joint, a replacement hip joint, a spinal device, etc.), a breast implant, a femoral rod, or desirably some other implantable medical device capable of collecting and providing in situ kinematic data, motion data, or other useful data.

[0074] The kinematic implantable device 1002 has one or more sensors for collecting information and kinematic data related to the use of the body part associated with the kinematic implantable device 1002. For example, the kinematic implantable device 1002 may desirably have an inertial measurement unit, such inertial measurement unit including a gyroscope, an accelerometer, a pedometer, or other kinematic sensors for collecting acceleration data with respect to the medial / lateral, anterior / posterior, and superior / inferior axes of the associated body part, angular velocity with respect to the sagittal, coronal, and transverse planes of the associated body part, and force, stress, tension, pressure, duress, displacement, vibration, flexion, stiffness, or some other measurable data.

[0075] The kinematic implantable device 1002 collects data at various different times and at various different rates during the patient monitoring process. In some embodiments, the kinematic implantable device 1002 can operate at a plurality of different stages throughout the patient monitoring course, that is, a lot of data is collected immediately after the kinematic implantable device 1002 is implanted into the patient's body, but the data collected when the patient is healed and thereafter is reduced.

[0076] In a non-limiting example, the monitoring process of the kinematic implantable device 1002 may include three different stages. The first stage may last for 4 months, in which case kinematic data is collected once a day for 1 minute every day of the week. After the first stage, the kinematic implantable device 1002 transitions to the second stage, which lasts for 8 months and collects kinematic data once a day for 1 minute on 2 days of the week. Then, after the second stage, the kinematic implantable device 1002 transitions to the third stage, in which it lasts for 9 years and collects kinematic data once a week for 1 minute over the next 9 years. Of course, the periods associated with each stage may be longer, shorter, or controllable in a different way, for example, the trachea may be selected to be compatible with the period specified by the medical insurance telemedicine code, so that as a result, the doctor sending the claim based on the telemedicine code can collect the maximum reimbursement amount allowed by the medical insurance company. The type and amount of data collected may also be controllable. An additional advantage of this passive monitoring process is that after the first monitoring stage, the patient does not know when the data is being collected. Thus, the data collected is protected from potential biases.

[0077] Together with different types of stages, the kinematic implantable device 1002 can operate in various modes to detect different types of movements. Thus, when a predetermined type of movement is detected, the kinematic implantable device 1002 can increase, decrease, or control in a different way the amount and type of kinematic data and other collected data.

[0078] In one embodiment, the kinematic implantable device 1002 can use a pedometer to determine whether a patient is moving. If it is measured that the number of steps defined by the kinematic implantable device 1002 exceeds a threshold within a predetermined time, the kinematic implantable device 1002 can determine that the patient is walking. In response to this determination, the amount and type of collected data can be started, stopped, increased, decreased, or appropriately controlled in a different way. The kinematic implantable device 1002 can further control data collection based on certain conditions, such as when the patient stops walking, when the selected maximum amount of data for the collection session has been collected, when the kinematic implantable device 1002 times out, or other conditions. After data is collected in a specific session, the kinematic implantable device 1002 can stop data collection until the next day, until the next time the patient walks, after the previously collected data has been offloaded (e.g., by transmitting the collected data to the home base station 1004), or according to one or more other conditions.

[0079] The amount and type of data collected by the kinematic implantable device 1002 may vary from patient to patient, and the amount and type of collected data may also change for a single patient. For example, medical personnel studying the data of a specific patient collected by the kinematic implantable device 1002 can adjust how the kinematic implantable device 1002 will collect future data or control it in a different way.

[0080] The amount and type of data collected by the kinematic implantable device 1002 may vary for different body parts, different types of movement, different patient demographics, or other differences. Alternatively or additionally, the amount and type of data collected may vary over time based on other factors such as how attentive or how the patient feels, how long the monitoring process is planned to last, how much battery power remains and how much should be stored, the type of movement being monitored, the body part being monitored, and the like. In some cases, the data collected is supplemented by personally descriptive information provided by the patient, such as subjective pain data, quality of life metric data, co-morbidities, perceptions or expectations the patient has related to the kinematic implantable device 1002.

[0081] In some embodiments, the kinematic implantable device 1002 is implanted into a patient's body to monitor the movement of a particular body part or other aspect. The implantation of the kinematic implantable 1002 into the patient's body may be done in an operating room. As used herein, "operating room" includes any clinic, room, building, or facility where the kinematic implantable device 1002 is implanted into a patient's body. For example, the operating room may be a typical operating room in a hospital, an operating room in a surgical clinic or a physician's office, or any other operating room where the kinematic implantable device 1002 is implanted into a patient's body.

[0082] An operating room base station (not shown in FIG. 3) is utilized to configure and initialize the kinematic implantable device 1002 in relation to the kinematic implantable device 1002 implanted in the patient's body. A communication relationship is established between the kinematic implantable device 1002 and the operating room base station based on, for example, a polling signal transmitted by the operating room base station and a response signal transmitted by the kinematic implantable device 1002.

[0083] When establishing a communication relationship, which often occurs before implanting the kinematic implantable device 1002, the operating room base station (not shown in FIG. 3) transmits initial configuration information to the kinematic implantable device 1002. Examples of this initial configuration information include, but are not limited to, a time stamp, a date stamp, an identification code for the type and placement of the kinematic implantable device 1002, information about other implants related to the kinematic implantable device, information about the surgeon, a patient identification code, information about the operating room, and the like.

[0084] In some embodiments, the initial configuration information is passed in one direction, and in other embodiments, the initial configuration is passed in both directions. The initial configuration information can define at least one parameter related to the collection of kinematic data by the kinematic implantable device 1002. For example, the configuration information can measure setting values (e.g., accelerometer range, accelerometer output data rate, gyroscope range, gyroscope output data rate, etc.) for one or more sensors provided in the kinematic implantable device 1002 for each of one or more operating modes. The configuration information may further include other control information, such as the initial operating mode of the kinematic implantable device 1002, specific movements that trigger a change in the operating mode, wireless settings, data collection information (e.g., how often the kinematic implantable device 1002 wakes up to collect data, how long the kinematic implantable device 1002 collects data, how much data to collect), identification information of the home base station 1004, the smart device 1005, and the connected mobile information terminal 1007, and other control information related to the implantation or operation of the kinematic implantable device 1002. Examples of the connected mobile information terminal 1007, also called a smart speaker, include Amazon Echo (registered trademark), Amazon Dot (registered trademark), Google Home (registered trademark), Philips (registered trademark), patient monitor, the health-tracking speaker of Comcast, and Apple HomePod (registered trademark).

[0085] In some embodiments, the configuration information may be pre - stored on an operating room base station (not shown in FIG. 3) or a related computing device. In other embodiments, a surgeon, surgical technician, or other healthcare provider may input control information and other parameters into the operating room base station for transmission to the kinematic implantable device 1002. In at least some such embodiments, the operating room base station may communicate with an operating room configuration computing device (not shown in FIG. 3). The operating room configuration computing device has an application with a graphical user interface that enables a healthcare provider to input configuration information regarding the kinematic implantable device 1002. In various embodiments, the application executed on the operating room configuration computing device may have some of the default configuration information, and such information may or may not be adjustable by the healthcare provider.

[0086] The operating room configuration computing device (not shown in FIG. 3) transmits the configuration information to the operating room base station (not shown in FIG. 3) via wired or wireless network connection means (e.g., USB connection means, Bluetooth® connection means, Bluetooth® Low Energy (BTLE) connection means, or Wi - Fi connection means), and this wired or wireless network connection means transmits this configuration information to the kinematic implantable device 1002.

[0087] The operating room setup computing device (not shown in FIG. 3) can also display information regarding the kinematic implantable device 1002 or the operating room base station (not shown in FIG. 3) to the surgeon, surgical technician, or other medical personnel. For example, the operating room setup computing device may display error information if the kinematic implantable device 1002 is unable to store or access configuration information, if the kinematic implantable device 1002 does not respond, if the kinematic implantable device 1002 identifies a problem with either the sensor or the wireless during an initial self-check, if the operating room base station (not shown in FIG. 3) does not respond or is malfunctioning, or for other reasons.

[0088] The operating room base station (not shown in FIG. 3) and the operating room setup computing device (not shown in FIG. 3) are illustrated as separate devices, but embodiments are not so limited; rather, the functions of the operating room setup computing device and the operating room base station can be included in a single computing device or in separate devices as illustrated. Thus, in one embodiment, medical personnel are enabled to directly input configuration information into the operating room base station.

[0089] Once the kinematic implantable device 1002 is implanted into a patient's body and the patient returns home, the home base station 1004, the smart device 1005 (e.g., the patient's smartphone), the connected mobile information terminal 1007, or two or more of the home base station, the smart device, and the connected mobile information terminal can communicate with the kinematic implantable device 1002. The kinematic implantable device 1002 can collect kinematic data at a defined rate and time, a variable rate and time, or a controlled rate and time. Data collection can start when the kinematic implantable device 1002 is initialized in the operating room, when directed by a healthcare provider, or at some later point in time. At least some of the data collected by the kinematic implantable device 1002 can be transmitted directly to the home base station 1004, directly to the smart device 1005, directly to the connected mobile information terminal 1007, transmitted to the base station via one or both of the smart device and the connected mobile information terminal, transmitted to the smart device via one or both of the base station and the connected mobile information terminal, or transmitted to the connected mobile information terminal via one or both of the smart device and the base station. In this case, the expression "one or both" means via an item alone or via both items, either sequentially or in parallel. For example, the data collected by the kinematic implantable device 1002 can be transmitted to the home base station 1004 directly via the smart device 1005 alone, directly via the connected mobile information terminal 1007 alone, continuously via the smart device and the connected mobile information terminal, continuously via the connected mobile information terminal and the smart device, directly via both the smart device and the connected mobile information terminal, and in some cases simultaneously.Similarly, the data collected by the kinematic implantable device 1002 can be transmitted continuously via the home base station 1004 alone, via the connected mobile information terminal 1007 alone, via the home base station and the connected mobile information terminal, continuously via the connected mobile information terminal and the home base station, directly via both the home base station and the connected mobile information terminal, and in some cases simultaneously to the smart device 1005. Further, in one embodiment, the data collected by the kinematic implantable device 1002 can be transmitted via the smart device 1005 alone, via the home base station 1004 alone, continuously via the smart device and the home base station, continuously via the home base station and the smart device, directly via both the smart device and the home base station, and in some cases simultaneously to the connected mobile information terminal 1007.

[0090] In various embodiments, one or more of the home base station 1004, the smart device 1005, and the connected mobile information terminal 1007 ping the kinematic implantable device 1002 at periodic times, predetermined times, or other times to determine whether the kinematic implantable device 1002 is within the communication range of one or more of the home base station, the smart device, and the connected mobile information terminal. Based on the response from the kinematic implantable device 1002, one or more of the home base station 1004, the smart device 1005, and the connected mobile information terminal 1007 can determine that the kinematic implantable device 1002 is within the communication range and issue a request, issue a command, or otherwise instruct to transmit the data collected by the kinematic implantable device 1002 to one or more of the home base station 1004, the smart device 1005, and the connected mobile information terminal 1007.

[0091] One or more of the home base station 1004, the smart device 1005, and the mobile information terminal 1007 in the connected state may each, in some cases, be provided with a user interface as an option. The user interface may be formed as a multimedia interface that passes one or more types of multimedia information (e.g., video, audio, tactile, etc.) in one direction or two directions. Through the respective user interfaces of one or more of the home base station 1004, the smart device 1005, and the mobile information terminal 1007 in the connected state, a patient (not shown in FIG. 3) or a patient's relative (not shown in FIG. 3) can enter other data to complement the kinematic data collected by the kinematic implantable device 1002. For example, the user can enter personal descriptive information (e.g., changes in age, changes in weight), changes in medical conditions, co-morbidities, pain levels, quality of life, an indicator of how the implanted prosthesis 1002 "feels", or other subjective metric data, a personal message for medical staff, etc. In these embodiments, the personal descriptive information can be entered by a keyboard, a mouse, a touch screen, a microphone, a wired or wireless computer interface, or some other input means. When collecting personal descriptive information, the personal descriptive information may include one or more identifiers that associate this information with unique identifiers of the kinematic implantable device 1002, the patient, the relevant medical staff, the relevant medical facility, etc., or can be associated with it in a different way.

[0092] In some of these cases, the user interface as an option for each of one or more of the home base station 1004, the smart device 1005, and the mobile information terminal 1007 in the connected state may also be configured to send information related to the kinematic implantable device 1002 from, for example, medical staff to the user. In these cases, the information sent to the user may be sent by a video screen, an audio output device, a tactile transducer, a wired or wireless computer interface, or some other similar means.

[0093] In various embodiments, one or more of the home base station 1004, the smart device 1005, and the mobile information terminal 1007 in a connected state may include a user interface, which may include an internal user interface configured to communicatively couple to a patient portal device. The patient portal device may be a smartphone, a tablet, a wearable device, a weight or other health measurement device (e.g., a thermometer, a scale, etc.), or any other computing device capable of wired or wireless communication. In these cases, the user may be able to enter personal descriptive information, and the user may also be able to receive information related to the implanted device 1002.

[0094] The home base station 1004 utilizes the patient's home network 1006 to transmit the collected data (i.e., kinematic data and in some cases personal descriptive information) to the cloud 1008. The home network 1006, which may be a local area network, provides access from the patient's home to a wide area network, such as the Internet. In some embodiments, the home base station 1004 can access the Internet by connecting to the home network 1006 using Wi-Fi connection means. In other embodiments, the home base station 1004 may be connected to a computer (not shown in FIG. 3) in the patient's home, for example, by USB connection means, and the USB connection means itself is connected to the home network 1006.

[0095] The smart device 1005 can communicate directly with the kinematic implantable device 1002, for example, by means of a Bluetooth (registered trademark) compliant signal, and can also transmit data collected using the patient's home network 1006 (i.e., kinematic data and in some cases personal descriptive information) to the cloud 1008, or can communicate directly with the cloud, for example, via a cellular network. As a variant, the smart device 1005 is configured to communicate directly with one or both of the mobile information terminals 1007 connected to the base station 1004, for example, by means of a Bluetooth (registered trademark) compliant signal, and this smart device is not configured to communicate directly with the kinematic implantable device 1002.

[0096] Furthermore, the connected mobile information terminal 1007 can communicate directly with the kinematic implantable device 1002, for example, by means of a Bluetooth (registered trademark) compliant signal, and can also transmit data collected using the patient's home network 1006 (i.e., kinematic data and in some cases personal descriptive information) to the cloud 1008, or can communicate directly with the cloud, for example, via a modem / Internet connection means or a cellular network. As a variant, the connected mobile information terminal 1007 is configured to communicate directly with one or both of the base station 1004 and the smart device 1005, for example, by means of a Bluetooth (registered trademark) compliant signal, and this smart device is not configured to communicate directly with the kinematic implantable device 1002.

[0097] Along with the transmission of the collected data to the cloud 1008, one or more of the home base station 1004, the smart device 1005, and the mobile information terminal 1007 in the connected state can also obtain data, commands, or other information directly from the cloud 1008 or via the home network 1006. One or more of the home base station 1004, the smart device 1005, and the mobile information terminal 1007 in the connected state can provide some or all of the received data, commands, or other information to the kinematic implant device 1002. Examples of such information include, but are not limited to, updated setting information, a diagnostic request for determining whether the kinematic implant device 1002 is functioning properly, a data collection request, and other information.

[0098] The cloud 1008 may include one or more server computers or databases to integrate the data collected from the kinematic implant device 1002 and possibly personal narrative information collected from a patient (not shown in FIG. 3) with the data collected from other kinematic implant devices (not shown) and possibly personal narrative information collected from other patients. Thus, the cloud 1008 can create various different metrics for the collected data from each of a plurality of kinematic implant devices implanted in separate patients. This information can be said to be useful in determining whether the kinematic implant device is functioning properly. The collected information can also be useful for other purposes, such as determining which particular device is not functioning properly, determining whether the procedures or conditions associated with the kinematic implant device are helping the patient (e.g., whether the replaced knee joint is operating correctly and relieving the patient's pain), and determining other medical information.

[0099] Throughout the monitoring process, at various times, the patient may be required to visit a healthcare provider to schedule follow-up observations. This healthcare provider may be the surgeon who implanted the kinematic implant device 1002 into the patient's body, or another healthcare provider who is overseeing the monitoring process, physical therapy, and the patient's recovery. For various different reasons, the healthcare provider may want to collect real-time data from the kinematic implant device 1002 in a controlled environment. In some cases, the request to visit the healthcare provider may be sent via a two-way user interface as an option for each of one or more of the home base station 1004, smart device 1005, and the connected mobile information terminal 1007.

[0100] The healthcare provider uses a base station of the physician's clinic (not shown in FIG. 3) that communicates with the kinematic implant device 1002 to transfer additional data between the physician's clinic base station and the kinematic implant device 1002. Alternatively or additionally, the healthcare provider uses the physician's clinic base station (not shown in FIG. 3) to send commands to the kinematic implant device 1002. In some embodiments, the physician's clinic base station instructs the kinematic implant device 1002 to enter a high-resolution mode, thereby temporarily increasing the rate or type of data collected over a short period of time. The high-resolution mode instructs the kinematic implant device 1002 to collect a different (e.g., more) amount of data during the activity in which the healthcare provider is also monitoring the patient.

[0101] In some embodiments, a physician's office base station (not shown in FIG. 3) enables healthcare providers to input an event or pain marker and synchronize such marker with the high-resolution data collected by the kinematic implantable device 1002. For example, assume that the kinematic implantable device 1002 is a component within a replacement knee joint. The healthcare provider may have the patient walk on a treadmill while the kinematic implantable device 1002 is in high-resolution mode. As the patient walks, the patient may complain about pain in their knee. The healthcare provider clicks a pain marker button on the physician's office base station to indicate the patient's discomfort. The physician's office base station records the marker and the time at which the marker was entered. Synchronizing the timing of this marker with the timing of the high-resolution data collected enables the healthcare provider to analyze the data to examine or investigate the cause of the pain.

[0102] In other embodiments, a physician's office base station (not shown in FIG. 3) can provide updated setting information to the kinematic implantable device 1002. The kinematic implantable device 1002 can store this updated setting information, and using this updated setting information, parameters related to the collection of kinematic data can be adjusted. For example, if a patient is recovering health, it is advisable for the healthcare provider to instruct a decrease in the frequency at which the kinematic implantable device 1002 collects data. Conversely, if a patient is experiencing unexpectedly intense pain, it is advisable for the healthcare provider to instruct the kinematic implantable device 1002 to collect additional data over a specified period (e.g., for several days). The healthcare provider may use the additional data to diagnose and address a particular problem. In some cases, the additional data may include personal descriptive information provided by the patient (not shown in FIG. 3), even after the patient has left the physician's office and is no longer within the range of the physician's office base station. In these cases, the personal descriptive information can be collected and transmitted via one or more of the home base station 1004, the smart device 1005, and the connected mobile information terminal 1007. The firmware within the kinematic implantable device and / or the base station provides safeguards to limit such enhanced monitoring durations so that the battery retains sufficient power over the implant's life cycle.

[0103] In various embodiments, a physician's office base station (not shown in FIG. 3) may communicate with a physician's office configured computing device (not shown in FIG. 3). The physician's office configured computing device includes an application with a graphical user interface that enables medical personnel to input commands and data. Some or all of the commands, data, and other information may later be transmitted via the physician's office base station to the kinematic implantable device 1002. For example, in some embodiments, a medical personnel can use the graphical user interface to command the kinematic implantable device 1002 to enter its high-resolution mode. In other embodiments, a medical personnel can use the graphical user interface to input or modify setting information for the kinematic implantable device 1002. The physician's office configured computing device transmits information (e.g., commands, data, or other information) to the physician's office base station via wired or wireless network connection means (e.g., USB connection means, Bluetooth® connection means, or Wi-Fi connection means), and the physician's office base station transmits some or all of the information to the kinematic implantable device 1002.

[0104] The physician's office setting computing device (not shown in FIG. 3) can also display other information regarding the kinematic implantable device 1002, other information regarding the patient (e.g., personal descriptive information), or other information regarding the physician's office base station to the healthcare provider. For example, the physician's office setting computing device can display high-resolution data collected by the kinematic implantable device 1002 and transmitted to a physician's office base station (not shown in FIG. 3). The physician's office setting computing device can also display error information if the kinematic implantable device 1002 is unable to store or access configuration information, if the kinematic implantable device 1002 is unresponsive, if the kinematic implantable device 1002 has detected a problem with either the sensor or the wireless, if the physician's office base station is unresponsive or malfunctioning, or for other reasons.

[0105] In some embodiments, the physician's office setting computing device (not shown in FIG. 3) may have access to the cloud 1008. In at least one embodiment, the healthcare provider can use the physician's office setting computing device to access data stored in the cloud 1008, such data having been previously collected by the kinematic implantable device 1002 and transmitted to the cloud 1008 via one or both of the home base station 1004 and the smart device 1005. Similarly, the physician's office setting computing device can transmit high-resolution data obtained from the kinematic implantable device 1002 to the cloud 1008 via the physician's office base station. In some embodiments, the physician's office base station can have Internet access and be able to directly transmit high-resolution data to the cloud 1008 without using the physician's office setting computing device.

[0106] In various embodiments, a healthcare provider can update the configuration information of the kinematic implantable device 1002 even when the patient is not within the healthcare provider's clinic. In these cases, the healthcare provider can use a physician's office setting computing device (not shown in FIG. 3) to transmit the updated configuration information to the kinematic implantable device 1002 via the cloud 1008. One or more of the home base station 1004, the smart device 1005, and the connected mobile information terminal 1007 can obtain the updated configuration information from the cloud 1008 or upload the updated configuration information to the cloud. Thereby, the healthcare provider can remotely adjust the operation of the kinematic implantable device 1002 without having to have the patient come to the healthcare provider's clinic. Also, thereby, the healthcare provider can send a message to the patient (not shown in FIG. 3) in response to, for example, personal narrative information provided by the patient and sent to a physician's office base station (not shown in FIG. 3) via one or more of the home base station 1004, the smart device 1005, and the connected mobile information terminal 1007. For example, if a patient with an artificial knee joint tells the connected mobile information terminal 1007 "my leg hurts when I walk", the healthcare provider can issue a prescription for painkillers and enable the connected mobile information terminal to "speak" to notify the patient that "the doctor has called the patient's preferred pharmacy to inform them that a prescription for Vicodin® will be available for pickup at 4:00 PM".

[0107] Although the physician's office base station (not shown in FIG. 3) and the physician's office setting computing device (not shown in FIG. 3) are described as separate devices, the embodiments are not limited to this. Rather, the functions of the physician's office setting computing device and the physician's office base station may be included in a single computing device or may be included in separate devices (as shown in the illustration). Thus, in one embodiment, it may be beneficial for the healthcare provider to be able to directly input configuration information or markers into the physician's office base station and view high-resolution data (and synchronized marker information) from the display of the physician's office base station.

[0108] Still referring to FIG. 3, alternative embodiments are contemplated. For example, one or two of the home base station 1004, the smart device 1005, and the mobile information terminal 1007 in the connected state may be omitted from the kinematic implantable device environment 1000. Further, each of the home base station 1004, the smart device 1005, and the mobile information terminal 1007 in the connected state may be configured to communicate with one or both of the implantable device 1002 and the cloud 1008 via another one or two of the base station, the smart device, and the mobile information terminal in the connected state. Further, the smart device 1005 may be temporarily contracted as an interface for the implantable prosthesis 1002, and such a smart device may be any suitable device other than a smartphone, for example, a smartwatch, a smart patch, and any IoT device that can act as an interface for the implantable device 1002, such as a coffee pot. Additionally, one or more of the base station 1004, the smart device 1005, and the mobile information terminal 1007 in the connected state can serve as a communication hub for a number of prostheses implanted in one or more patients. Further, one or more of the base station 1004, the smart device 1005, and the mobile information terminal 1007 in the connected state can automatically order or reorder a prescription or medical supply (e.g., a knee brace) in response to a patient input or an input of the implantable prosthesis (e.g., pain level, instability level), provided that a medical professional and an insurance company have pre-approved such an order or reorder. As a variant, one or more of the base station, the smart device, and the mobile information terminal in the connected state may be configured to request approval from a medical professional or an insurance company to place an order or reorder. Further, one or more of the base station 1004, the smart device 1005, and the mobile information terminal 1007 in the connected state may be equipped with a mobile information terminal, for example, Alexa (registered trademark) or Siri (registered trademark). Additionally, one or more alternative embodiments described below in connection with FIGS. 4-27 may be applicable to the kinematic implantable device environment 1000.

[0109] Figure 4 is a schematic diagram of an implantable circuit 1010 provided within or configured to be used in conjunction with an alert kinematic implant, such as an artificial knee joint implantable as part of a total knee arthroplasty (TKA).

[0110] Circuit 1010 is powered by a battery or other suitable implantable power source 1012 and includes a fuse 1014, switches 1016, 1018, a clock generator and power management unit 1020, an inertial measurement unit (IMU) 1022, a memory circuit 1024, a radio frequency (RF) transceiver 1026, an RF filter 1028, an RF compliant antenna 1030, and a control circuit 1032. Examples of some or all of these components are described elsewhere in this application or in U.S. Patent Application No. 16 / 084,544, which is hereby incorporated by reference in its entirety and made a part of this specification.

[0111] Battery 1012 can be any suitable battery, such as a lithium carbon monofluoride (LiCFx) battery configured to store energy to power circuit 1000 over the expected life of the kinematic implant (e.g., 5 to 25+ years), or other rechargeable battery.

[0112] Fuse 1014 can be any suitable fuse (e.g., a permanent fuse) or circuit breaker (e.g., a resettable circuit breaker) configured to prevent current flowing from battery 1012 from injuring the patient and damaging the battery and one or more components of circuit 1000. For example, fuse 1014 can be configured to prevent battery 1012 from generating enough heat to burn the patient, damage circuit 1000, damage the battery, or damage the structural components of the kinematic implant.

[0113] Switch 1016 is configured to couple and decouple battery 1012 to and from IMU 1022 in response to control signals from control circuit 1032. For example, control circuit 1032 may open switch 1016 during a sleep mode or other low power mode to conserve power in order to extend the life of battery 1012, thus disconnecting power from IMU 1022 by this switch, and thus may be configured to generate a control signal having an open state. Similarly, control circuit 1032 may also close switch 1016 and thus may be configured to generate a control signal having a closed state that couples power to IMU 1022 when this switch "wakes up" from the sleep mode or exits another low power mode. Such low power modes may be for only the IMU 1022 of the implantable circuit 1010 or may be for the IMU and one or more other components.

[0114] Switch 1018 is configured to couple and decouple battery 1012 to and from memory circuit 1024 in response to control signals from control circuit 1032. For example, control circuit 1032 may open switch 1018 during a sleep mode or other low power mode to conserve power in order to extend the life of battery 1012, thus disconnecting power from memory 1024 by this switch, and thus may be configured to generate a control signal having an open state. Similarly, control circuit 1032 may also close switch 1018 and thus may be configured to generate a control signal having a closed state that couples power to memory 1024 when this switch "wakes up" from the sleep mode or exits another low power mode. Such low power modes may be for only the memory circuit 1024 of the implantable circuit 1010 or may be for the memory circuit and one or more other components.

[0115] The clock and power management circuit 1020 may be configured to generate a clock signal for one or more of the other components of the embedded circuit 1010, and to generate periodic commands or other signals (e.g., interrupt requests) in response to one or more components of the embedded circuit entering or exiting sleep or other low-power modes by the control circuit 1032. The clock and power management circuit 1020 may also be configured to regulate the voltage from the battery 1012 and provide a constant power voltage to some or all of the other components of the embedded circuit 1010.

[0116] The IMU 1022 has a coordinate system with coordinate axes x-axis, y-axis, and z-axis, and the IMU may be configured to measure or otherwise quantify the acceleration experienced by the IMU along each of the x-axis, y-axis, and z-axis, and the angular velocity experienced by the IMU about each of the x-axis, y-axis, and z-axis. Such a configuration of the IMU 1022 is at least a 6-axis form since the IMU 1022 measures the six unique quantities, acc x (t), acc y (t), acc z (t), Ω x (t), Ω y (t), Ω z (t). As a variant, the IMU 1022 may be configured in a 9-axis form, in which case the IMU is acc x (t), acc y (t), acc z (t), Ω x (t), and Ω yIt may be beneficial to use gravity to compensate for the cumulative error of (t) or correct it in a different way. However, in embodiments where the IMU measures acceleration and angular velocity over a very short burst (e.g., 0.10 to 100 seconds (s)), for many applications, the cumulative error can typically be ignored without exceeding the respective error tolerance. IMU1022 may include a respective analog-to-digital converter (ACD) for each of the x, y, and z accelerometers or gyroscopes. As a variant, IMU1022 may include a respective sample-and-hold circuit for each of the x, y, and z accelerometers and gyroscopes and only a few ADCs, such as one, shared by the accelerometers and gyroscopes. By providing one or fewer ADCs per accelerometer and gyroscope, one or both of the size and circuit density of IMU1022 can be reduced, and moreover, the power consumption of the IMU can be reduced. However, since IMU1022 includes a respective sample-and-hold circuit for each accelerometer and gyroscope, samples of the analog signals generated by the accelerometers and gyroscopes can be taken at the same or different sample times, at the same or different sample rates, and moreover, at the same or different output data rates (ODR).

[0117] Memory circuit 1024 may be any suitable non-volatile memory circuit, such as an EEPROM or FLASH (registered trademark) memory, which is configured to store data written by control circuit 1032 and provide data in response to a read command from the control circuit.

[0118] The RF transceiver 1026 can be a conventional transceiver configured to communicate with a base station (not shown in FIG. 4) in which the control circuit 1032 (and optionally the fuse 1014) can be applied to a kinematic implantable device. For example, the RF transceiver 1026 can be a transceiver of any suitable type (e.g., Bluetooth®, Bluetooth® Low Energy (BTLE), and Wi-Fi®), and this RF transceiver can be configured to operate in accordance with any suitable protocol (e.g., MICS, ISM, Bluetooth®, Bluetooth® Low Energy (BTLE), and Wi-Fi®), and is preferably configured to operate in a frequency band within the range from 1 MHz to 5.4 GHz, or within any other suitable range.

[0119] The filter 1028 can be any suitable bandpass filter, for example, a surface acoustic wave (SAW) or bulk acoustic wave (BAW) filter.

[0120] The antenna 1030 can be any antenna suitable for the frequency band in which the RF transceiver 1026 can generate signals transmissible by the antenna, and the frequency band in which a base station (not shown in FIG. 4) can generate signals receivable by the antenna.

[0121] A control circuit 1032, which may be any suitable implantable report processor (IRP), such as a microcontroller or a microprocessor, is configured to control the configuration and operation of one or more of the other components of the implantable circuit 101. For example, the control circuit 1032 controls the IMU 1022 to measure the movement of the implantable prosthesis associated with the implantable circuit 1010, quantifies the quality of such measurements (e.g., whether the measurement is "good" or "bad"), thereby causing the measurement data generated by the IMU to be stored in the memory 1024, generating a message containing the stored data as a payload, and packetizing this message, thereby providing the message packet to the RF transceiver 1026 for transmission to a base station (not shown in FIG. 4). The control circuit 1032 is also preferably configured to execute commands received from a base station (not shown in FIG. 4) via the antenna 1030, the filter 1028, and the RF transceiver 1026. For example, the control circuit 1032 may be configured to receive configuration data from a base station and provide this configuration data to the components of the implantable circuit 1010 to which the base station directs the configuration data. If the base station directs configuration data to the control circuit 1032, the control circuit is configured to configure itself in response to the configuration data.

[0122] Still referring to FIG. 4, the operation of the circuit 1010 will be described according to an embodiment in which an implantable prosthesis in which the circuit 1010 is housed or an implantable prosthesis in which the circuit 1010 is associated in a different way is implanted into a patient (not shown in FIG. 4).

[0123] The fuse 1014, which is normally electrically closed, is configured to open electrically in response to an event that may harm the patient in whom the implanted circuit 1010 is implanted, or an event that may damage the battery 1012 of the implanted circuit if this event continues beyond a safe period. Events in which the fuse 1014 may open electrically include an overcurrent state, an overvoltage state, an over-temperature state, an overcurrent time state, an overvoltage time state, and an over-temperature time state. The overcurrent state occurs in response to a current passing through the fuse 1014 that exceeds an overcurrent threshold. Similarly, the overvoltage state occurs in response to a voltage applied across the fuse 1014 that exceeds an overvoltage threshold, and the over-temperature state occurs in response to a temperature of the fuse that exceeds a temperature threshold. The overcurrent time state occurs in response to an integrated value of the current passing through the fuse 1014 over a measurement time window (e.g., 10 seconds) that exceeds a current time threshold, where in this case the window can "slide" forward in time such that the window extends back from the current time to the length of the window (in units of time). As a variant, the overcurrent time state occurs when the current passing through the fuse 1014 exceeds the overcurrent threshold for a time that exceeds a threshold time. Similarly, the overvoltage time state occurs in response to an integrated value of the voltage applied across the fuse 1014 over a measurement time window, and the over-temperature time state occurs in response to an integrated value of the temperature of the fuse over a measurement time window. As a variant, the overvoltage time state occurs when the voltage applied across the fuse 1014 exceeds the overvoltage threshold for a time that exceeds a threshold time, and the over-temperature time state occurs when the temperature associated with the fuse 1014, battery 1012, or implanted circuit 1010 exceeds the over-temperature threshold for a time that exceeds a threshold time. However, even if the fuse 1014 opens, i.e., even if power is disconnected from the implanted circuit 1010, the mechanical and structural components of the kinematic prosthesis (not shown in FIG. 4) associated with the implanted circuit remain fully operational.For example, when the kinematic prosthesis is an artificial knee joint, the artificial knee joint can still function adequately as the patient's knee joint, but the lost function is to detect the kinematic movement of the prosthesis, measure it, thereby generating data representing the measured kinematic movement and storing it, and providing the stored data to a base station or other destination located outside the kinematic prosthesis. The operation of the fuse will be further described below in connection with FIG. 27.

[0124] The control circuit 1032 is configured to cause the movement over a time window (e.g., 10 seconds, 20 seconds, 1 minute) to be measured in response to the movement of the kinematic prosthesis to which the implanted circuit 1010 is associated with the IMU 1022, determine whether the measured movement is a quantified movement, store the data representing the measured quantified movement, and cause the data stored in the RF transceiver 1026 to be transmitted to a base station or other source located outside the prosthesis.

[0125] For example, IMU 1022 may be configured to start sampling the detection signals output from one or more of its accelerometers or one or more of its gyroscopes in response to the movement detected within each period (number of days). The control circuit 1032 may analyze the samples to determine whether the detected movement is a quantified movement. Further, in an embodiment, IMU 1022 can detect movement by any conventional method, for example, by one or more movements of one or more of its accelerometers. In response to the IMU 1022 communicating the detected movement to the control circuit 1032, the control circuit can correlate the samples from the IMU to the stored accelerometer and gyroscope samples generated by computer simulation, or while the patient or another patient is walking normally, the control circuit can measure the time during which the movement continues (this time is equal to the number of samples multiplied by the inverse matrix of the sample rate). If the samples of the output signals of the accelerometer and gyroscope correlate with the respective stored samples and the time during which the movement continues is longer than the threshold time, the control circuit 1032 effectively labels this movement as a quantified movement.

[0126] In response to a determination that the movement is a quantified movement, the control circuit 1032 stores the sample in the memory circuit 1024 together with other data, and opens the switch 1016 to disable the IMU 1022 until the next period (e.g., the next day or the next week) to extend the life of the battery 1012. The clock and power management circuit 1020 may be configured to generate a periodic timing signal, e.g., an interrupt, to start each period. For example, the control circuit 1032 can close the switch 1016 in response to such a timing signal from the clock and power management circuit 1020. Further, as other data, for example, each sample rate for each set of accelerometer and gyroscope samples, each time stamp indicating the time when the IMU 1022 collected the corresponding set of samples, each sample time for each set of samples, an identifier of the implantable prosthesis (e.g., serial number), and a patient identifier (e.g., number or name) can be mentioned. The volume of other data can be significantly reduced if the sample rate, time stamp, and sample time are the same for each set of samples (i.e., samples of signals from all accelerometers and gyroscopes taken at the same rate at the same time), because the header for all sets of samples includes only one sample rate, only one time stamp, and only one set of sample times. Further, the control circuit 1032 may encrypt some or all of the data in a conventional manner before storing the data in the memory 1024. For example, the control circuit 1032 may dynamically encrypt some or all of the data such that the same data has a different encryption form at any given time than when it was encrypted at another time.

[0127] As further described below in connection with FIGS. 9-24 and elsewhere in the present application, stored data samples of signals generated by one or more accelerometers and one or more gyroscopes of the IMU 1022 can provide clues as to the state of the implantable prosthesis. For example, the data samples can be analyzed (e.g., by a remote server, such as a cloud server) to determine whether the surgeon has implanted the prosthesis accurately, to determine the level of instability and degradation exhibited by the implanted prosthesis at the current time, to determine the instability and degradation profile over time, and to compare the instability and degradation profile to a benchmark instability and degradation profile generated from statistical simulations or data from a statistically significant patient group.

[0128] Furthermore, the sample rate, output data rate (ODR), and sampling frequency of the IMU 1022 may be set to any appropriate values. For example, the sample rate may be any appropriate value, e.g., fixed at 3200 Hz, and the ODR, which may be below the sample rate and which results from periodically "dropping" samples, may be any appropriate value, e.g., 800 Hz. The sampling frequency (the reciprocal of the time interval between sampling periods) for limited events may be any appropriate value, e.g., twice a day, once a day, once every two days, once a week, once a month, or more or less frequently than this. Also, the sample rate or ODR can be varied according to the type of event during sampling. For example, to detect that a patient is walking without the patient analyzing the implant for the patient's walking or instability or wear, the sample rate or ODR may be 200 Hz, 25 Hz or less. Thus, using such a low-resolution mode, an indication (that the patient is walking several steps with the artificial knee joint) of a limited event (that the patient walks at least 10 consecutive steps) can be detected because the "search" for the limited event may include a number of false detections before the limited event is detected. By using a low sample rate or ODR, the IMU 1022 saves power while performing the search and increases the sample rate or ODR (e.g., to 800 Hz, 1600 Hz, or 3200 Hz) only to sample the detected limited event, so that the accelerometer and gyroscope signals then have a sampling resolution sufficient for analyzing samples for, e.g., prosthesis instability and wear.

[0129] Still referring to FIG. 4, in response to being polled by a base station (not shown in FIG. 4) or by another device located external to the implanted prosthesis, control circuit 1032 generates a legacy message having a payload and a header. The payload includes samples of the stored state of the signals generated by the accelerometer and gyroscope of IMU 1022, and the header includes sample partitioning in the payload (i.e., which bit positions the samples of the x-axis accelerometer are placed in, which bit positions the samples of the x-axis gyroscope are placed in, etc.), the respective sample rates for each set of accelerometer and gyroscope samples, a time stamp indicating the time when IMU 1022 collected the samples, an identifier of the implantable prosthesis (e.g., serial number), and a patient identifier (e.g., number or name).

[0130] Control circuit 1032 generates data packets including messages compliant with a legacy data packetization protocol. Each packet may further include a packet header including, for example, a sequence number of the packet, such that the receiving device can correctly order the packets even if they are sent or received out of order.

[0131] Control circuit 1032 encrypts some or all parts of each of the data packets according to, for example, a legacy encryption algorithm, and the error encodes the encrypted data packets. For example, control circuit 1032 encrypts at least the identifiers of the prosthesis and the patient to bring the data packets into compliance with the Health Insurance Portability and Accountability Act (HIPAA).

[0132] The control circuit 1032 provides the encrypted and error-coded data packet to the RF transceiver 1026, which sends the data packet via the filter 1028 and the antenna 1030 to a destination located outside the implantable prosthesis, such as the base station 1004 (Figure 3). The RF transceiver 1026 can send the data packet in accordance with any suitable data packet transmission protocol.

[0133] Still referring to Figure 4, a modified embodiment of the implantable circuit 1010 is envisioned. For example, the RF transceiver can perform encryption or error coding instead of or complementary to the control circuit 1032. Further, one or both of the switches 1016, 1018 can be omitted from the implantable circuit 1010. Additionally, the implantable circuit 1010 can include components other than those described herein and can omit one or more of the components described herein. Moreover, one or more of the embodiments described in connection with Figures 3 and 5 - 27 can be utilized with the implantable circuit 1010.

[0134] Figure 5 is a schematic diagram of a base station circuit 1040 configured to be communicable with the implantable circuit 1010 of Figure 4 according to one embodiment, for example, provided within or configured to be used with the home base station 1004 of Figure 3.

[0135] The base station circuit 1040 is powered by a power supply 1042 and includes first and second antennas 1044, 1046, first and second RF filters 1048, 1050, first and second RF transceivers 1052, 1054, a memory circuit 1056, and a base station control circuit 1058. Examples of some or all of these components are described elsewhere in this application or in U.S. Patent Application No. 16 / 084,544, which is hereby incorporated by reference in its entirety in all jurisdictions under the relevant legal authority and the description thereof is made a part of this specification.

[0136] Power supply 1042 may be any suitable power supply, for example, a battery or a power supply that receives power from an electrical outlet. If the power supply is of the latter type, the power supply may further include a battery backup for use during a power outage or when the base station circuit 1040 is "unplugged".

[0137] Antenna 1044 may be any antenna suitable for the frequency band in which RF transceiver 1052 communicates with the implanted circuit 1010 of FIG. 4.

[0138] Similarly, antenna 1046 may be any antenna suitable for the frequency band in which RF transceiver 1054 communicates with components of the home network 1006 of FIG. 3, such as a Wi-Fi® router, access point, or repeater.

[0139] Each of filters 1048, 1050 may be any suitable bandpass filter, for example, a surface acoustic wave (SAW) filter or a bulk acoustic wave (BAW) filter.

[0140] RF transceiver 1052 may be a conventional transceiver configured to enable control circuit 1058 to communicate with implanted circuit 1010 of FIG. 4 while the implant circuit is provided within an implantable prosthesis, such as the kinematic implantable device 1002 of FIG. 3, or while otherwise associated therewith. For example, RF transceiver 1052 may be a transceiver of any suitable type (e.g., Bluetooth®, Bluetooth® Low Energy (BTLE), and Wi-Fi®), may be operably configured to comply with any suitable protocol (e.g., MICS, ISM, Bluetooth®, Bluetooth® Low Energy (BTLE), and Wi-Fi®), and may be operably configured to operate in a frequency band ranging from 1 MHz to 5.4 GHz or within any other suitable range.

[0141] Similarly, the RF transceiver 1054 can be any conventional transceiver configured such that the control circuit 1058 can communicate with, for example, a Wi-Fi (registered trademark) router, access point, or repeater of the home network 1006 in FIG. 3, or with one or more of the home base station 1004, smart device 1005, and mobile information terminal 1007 in a connected state in FIG. 3. For example, the RF transceiver 1054 can be a transceiver in any suitable form (e.g., Bluetooth (registered trademark), Bluetooth (registered trademark) Low Energy (BTLE), and Wi-Fi (registered trademark)), can be configured to operate in accordance with any suitable protocol (e.g., MICS, ISM, Bluetooth (registered trademark), Bluetooth (registered trademark) Low Energy (BTLE), and Wi-Fi (registered trademark)), and can also be configured to operate in a frequency band ranging from 1 MHz to 5.4 GHz or within any other suitable range.

[0142] The memory circuit 1056 can be any suitable non-volatile memory circuit, such as an EEPROM or FLASH (registered trademark) memory, and this memory circuit is preferably configured to store data written by the control circuit 1058 and provide data in response to a read command from the control circuit. For example, the control circuit 1058 can cause the memory 1056 to store a data packet received from the implanted circuit 1010 in FIG. 4, and can also cause the memory to store a data packet received from a cloud server via the RF transceiver 1054. In this case, the data packet includes, for example, a command, instruction, or configuration data for the implanted circuit 1010 in FIG. 4. As a variant, the memory 1056 can be a volatile memory.

[0143] The base station control circuit 1058, which can be any suitable processor, such as a microcontroller or a microprocessor, is configured to control its own configuration and operation as well as the configuration and operation of one or more of the other components of the base station circuit 1040. For example, the base station control circuit 1058 may be configured to receive data packets from the implantable circuit 1010 of FIG. 4 via the RF transceiver 1052, convert the received data packets into data packets suitable for transmission to the home network 1006 of FIG. 3, and transmit the converted data packets to the home network via the RF transceiver 1054. And the base station control circuit 1058 may also be configured to receive data packets from the home network 1006 via the RF transceiver 1054, convert the received data packets into data packets suitable for transmission to the implantable circuit 1010, and transmit the converted data packets to the implantable circuit via the RF transceiver 1052.

[0144] Still referring to FIG. 5, the operation of the base station circuit 1040 according to an embodiment in which an implantable prosthesis (not shown in FIG. 5), which is a communication partner of the base station circuit, is implanted in a patient (not shown in FIG. 5) will be described.

[0145] The control circuit 1058 polls the implantable circuit 1010 (FIG. 4) of the implantable prosthesis (not shown in FIG. 5) at regular intervals, for example, once a day, once every other day, once a week, or once a month. If the control circuit 1058 does not receive a response to the polling, the control circuit may poll the implantable circuit 1010 more frequently (e.g., every 5 minutes, every 30 minutes, every hour) until the control circuit receives a response or determines that the implantable prosthesis is outside the communication range of the base station.

[0146] The implantable circuit 1010 (FIG. 4) responds to the polling by transmitting all of the data packets of the IMU samples generated since the transmission of the last data packet.

[0147] The antenna RF transceiver 1052 receives data packets from the implanted circuit 1010 (FIG. 4) via the antenna 1044 and the filter 1048, and provides the received data packets to the base station control circuit 1058. This base station control circuit decodes and decrypts the data packets, analyzes the message from the data packets, and stores the analyzed message in the memory circuit 1056. Before storing the analyzed message, the base station control circuit 1058 may encrypt some or all of each analyzed message for HIPAA compliance.

[0148] Next, the base station control circuit 1058 reformats the stored message or creates a new message in response to the headers and payloads of the stored messages. For example, the base station control circuit 1058 can create a new message that includes each payload and header from the messages it received, but each includes additional header information, such as an identifier of the base station 1004 (FIG. 4), the time of receipt of the original message from the implanted circuit 1010 (FIG. 4), and the time of creation of the new message.

[0149] Before creating a new message, the base station control circuit 1058 may decrypt the analyzed message stored in the memory 1056.

[0150] The base station control circuit 1058 then creates a data packet containing a new message, encrypts some or all of each data packet, and error-codes the data packet, and provides the encrypted and coded data packet to the RF transceiver 1054, which transmits the encrypted and coded data packet to the home network 1006 via the filter 1050 and the antenna 1046. The base station control circuit 1058 may temporarily store the encrypted and coded data packet in the memory 1056 (e.g., in a buffer), and then provide the data packet to the RF transceiver 1054.

[0151] In a variant embodiment, the base station control circuit 1058 "passes" the data packet received from the implantable circuit 1010 (FIG. 4) to the home network 1006 (FIG. 3). That is, the base station control circuit 1058 receives one or more data packets from the implantable circuit 1010 via the RF transceiver 1052, temporarily stores the one or more data packets in the memory 1056, and causes the RF transceiver 1054 to transmit the one or more data packets to the home network 1006.

[0152] In yet another variant, the control circuit 1058 modifies one or more data packets received from the implantable circuit 1010 (FIG. 4) by first not analyzing one or more data packets or analyzing only a percentage rather than all of each data packet.

[0153] The home network 1006 (FIG. 3) may "pass" one or more data packets received from the base station 1004 to a destination, such as a server on the cloud 1008 (FIG. 3), or may modify one or more data packets according to an appropriate communication protocol before sending the one or more data packets to the destination.

[0154] The operation of the base station circuit 1040 will be further described in connection with FIG. 26.

[0155] Still referring to FIG. 5, a modified embodiment of the base station circuit 1040 is envisioned. For example, the embodiments described in connection with FIGS. 3, 4, and 6-27 can be utilized for the base station circuit 1040.

[0156] FIG. 6 is a perspective view of the IMU 1022 of FIG. 4 according to one embodiment. For example, the IMU 1022 may be a Bosch BMI 160 small low-power IMU.

[0157] As described above in connection with FIG. 4, the IMU 1022 has three measurement axes 1060, 1062, 1064, which are arbitrarily labeled x, y, z for purposes of explanation. That is, in the Cartesian coordinate system, the labels "x", "y", and "z" can be arbitrarily adapted to the axes 1060, 1062, 1064 in any order or arrangement. The mark 1066 is a reference indicating the location and orientation of the axes 1060, 1062, 1064 with respect to the IMU 1022 package.

[0158] The IMU 1022 includes three accelerometers (not shown in FIG. 6), each of which detects and measures the acceleration a(t) along each axis 1060 (x), 1062 (y), 1064 (z), where a x (t) is the acceleration along the x-axis, and a y (t) is the acceleration along the y-axis, and a z (t) is the acceleration along the z-axis. Each accelerometer produces a respective analog detection or output signal representing the instantaneous amplitude of the acceleration detected along the corresponding axis. For example, the amplitude of the accelerometer output signal at a given point in time is proportional to the magnitude of the acceleration along the detection axis of the accelerometer at the same point in time.

[0159] The IMU 1022 further includes three gyroscopes (not shown in FIG. 6), each of which detects and measures the angular velocity Ω(t) about each axis 1060 (x), 1062 (y), 1064 (z), where Ω xω(t) is the angular velocity about the x-axis, and Ω y ω(t) is the angular velocity about the y-axis, and Ω z ω(t) is the angular velocity about the z-axis. Each gyroscope generates a respective analog detection or output signal representing the instantaneous amplitude of the angular velocity detected about the corresponding axis. For example, the amplitude of the gyroscope output signal at a given point in time is proportional to the magnitude of the angular velocity about the detection axis of the gyroscope at the same point in time.

[0160] IMU 1022 includes at least two analog-to-digital converters (ADCs) (not shown in FIG. 6) for each of the axes 1060, 1062, 1064. One ADC converts the output signal of the corresponding accelerometer into a corresponding digital acceleration signal, and the other ADC converts the output signal of the corresponding gyroscope into a corresponding digital angular velocity signal. For example, each of the ADCs may be an 8-bit, 16-bit, or 24-bit ADC.

[0161] The circuit designer may configure each ADC (not shown in FIG. 6) to have respective parameter values that are the same as or different from the parameter values of the other ADCs. Examples of such parameters having set values include sample rate, dynamic range at the ADC input node, and output data rate (ODR). One or more of these parameters may be set to a fixed value, and one or more of the other of these parameters may be dynamically configurable (e.g., during runtime). For example, the respective sample rate of each ADC may be dynamically configurable such that during one sampling period, the sample rate has one value and during another sampling period, the sample rate has another value.

[0162] For each digital acceleration signal and each digital angular velocity signal, the IMU 1022 may be configured to provide parameter values associated with this signal. For example, the IMU 1022 may provide a sample rate, a dynamic range, and a time stamp indicating the time when the first sample or the last sample was taken, for each digital acceleration signal and each digital angular velocity signal. The IMU 1022 may be configured to provide these parameter values in the form of a message header (the corresponding sample from the message payload) or in any other suitable form.

[0163] Still referring to FIG. 6, a modified embodiment of the IMU 1022 is envisioned. For example, the IMU 1022 can have a shape other than square or rectangular. Further, the embodiments described in connection with FIGS. 3-5 and FIGS. 7-27 can be utilized with the IMU 1022.

[0164] FIG. 7 is a front view of a standing male patient 1070 having an artificial knee joint 1072 implanted to replace the left knee joint, and the axes 1060, 1062, 1064 (arbitrarily labeled x, y, z) of the IMU 1022 (FIG. 6), according to one embodiment.

[0165] FIG. 8 is a side view of the patient 1070 of FIG. 7 in an upright posture and the axes 1060, 1062, 1064 (arbitrarily labeled x, y, z) of the IMU 1022 (FIG. 6), according to one embodiment. The artificial knee joint 1072 is shown across the patient's right leg.

[0166] Referring to FIGS. 7 and 8, in one embodiment, ideally one IMU axis (the x-axis 1060 in FIGS. 7 and 8) is perpendicular for the patient 1070, while the patient 1070 stands straight, and one IMU axis (the y-axis 1062 in FIGS. 7 and 8) is the axis that becomes the center or is parallel when the artificial knee joint rotates and bends, and the remaining IMU axis (the z-axis 1064 in FIGS. 7 and 8) is perpendicular to the other two axes, and in this case all three axes intersect at the origin of the coordinate system.

[0167] There are many techniques that assist a surgeon implanting the artificial knee joint 1072 in aligning the IMU axes 1060, 1062, 1064 in the direction of the ideal axes. First, the orientation of the IMU 1022 (FIG. 6) in the tibial extension (described elsewhere herein) is fixed within a relatively tight tolerance range from extension to extension during the process of assembling the tibial extension by the physical design of the components. Second, both the tibial extension and the tibial base plate (described elsewhere in this specification) include alignment markers that a surgeon uses to align the tibial extension with the tibial base plate components during the procedure for implanting the artificial knee joint, such that the extension-plate alignment is within a relatively tight tolerance for each implant. Third, the uniformity of the tibial head for each patient and the uniformity of how the surgeon modifies the tibial head to receive the tibial base plate fix the orientation of the tibial base plate components within a relatively tight tolerance for each patient.

[0168] Despite these axis-alignment techniques, the IMU axes 1060, 1062, 1064 may be misaligned with respect to the ideal axis alignment described above. For example, such misalignment may have one or both of a translational component and a rotational component, where the rotational component is typically more influential than the translational component. Further, in an embodiment, the rotational misalignment may range from approximately a fraction of 1° to approximately 90°.

[0169] Techniques for compensating for or correcting such axis misalignment are described elsewhere in this application.

[0170] Still referring to FIGS. 7 and 8, alternative embodiments of the axis orientations and axis-orientation techniques described above are envisioned. For example, the axis orientations described above may be modified with respect to another type of implanted prosthesis, such as an artificial shoulder joint or an artificial hip joint. Further, the embodiments described in connection with FIGS. 3-6 and FIGS. 9-27 are applicable to the axis orientations and axis-orientation techniques described above.

[0171] Figure 9 shows, according to one embodiment, the analog acceleration signals a x (t), a y (t), a z (t) (units are m / s 2 ) generated by the accelerometer of the IMU 1022 (FIG. 4) in response to the acceleration along the x-axis 1060, y-axis 1062, and z-axis 1064 (FIG. 6) while the patient 1070 (FIGS. 7 and 8) walks forward at a normal pace for a period of about 10 seconds. In the above-described embodiment, the x-axis, y-axis, and z-axis have the ideal alignment described in connection with FIGS. 7 and 8, the artificial knee joint 1072 (FIGS. 7 and 8) has little or no degradation caused by instability or wear, and the IMU 1022 samples each of the analog acceleration signals a x (t), a y (t), a z (t) at the same sample time, the sample rate is 3200 Hz, and the output data rate (ODR) is 800 Hz. The ODR is the rate of the samples output by the IMU 1022 and is generated by downsampling the samples taken at 3200 Hz. That is, since 3200 Hz / 800 Hz = 4, the IMU 1022 generates an 800 Hz ODR by outputting only every fourth sample taken at 3200 Hz.

[0172] Figure 10 shows, according to one embodiment, the analog angular velocity signals Ω x (t), Ω y (t), Ω z (t) (units m / s 2) is a plot 1080 representing the relationship between digitization and time. In the above-described embodiment, the x-axis, y-axis, and z-axis have the ideal alignment described in connection with FIGS. 7 and 8, the artificial knee joint 1072 (FIGS. 7 and 8) has little or no degradation caused by instability or wear, and the IMU 1022 has the analog angular velocity signals Ω x (t), Ω y (t), Ω z (t), and the analog acceleration signals a x (t), a y (t), a z (t) are each sampled at the same sample time, with the same sample rate of 3200 Hz and the same ODR of 800 Hz. That is, plot 1082 is time-aligned with plot 1080 of FIG. 9.

[0173] FIG. 11 shows, according to one embodiment, an intermediate portion 1084 of plot 1080 of FIG. 9 with an expanded (i.e., high-resolution) time scale and events related to walking marked. For example, the times when the heel of patient 1070 (FIGS. 7 and 8) hits the surface on which the patient is walking and when the patient lifts the toes off the surface are marked. Further, the intermediate portion 1084 excludes the start portion of plot 1080 representing the period during which patient 1070 is accelerating to his normal walking speed and the end portion of plot 1080 representing the period during which the patient is decelerating to a stop, and thus represents the period during which the patient is walking at a substantially constant speed.

[0174] FIG. 12 shows, according to one embodiment, an intermediate portion 1086 of plot 1082 of FIG. 10 that includes the same expanded (i.e., high-resolution) time scale as the graph (plot) 1084 of FIG. 11. For example, the times when the heel of patient 1070 (FIGS. 7 and 8) hits the surface on which the patient is walking, when the patient lifts the toes off the surface, and the peak angular velocity Ω of the knee joint when the artificial knee joint bends about the y-axis (or about an axis substantially parallel to the y-axis) y(t) is marked with a time. Further, the middle portion 1086 excludes the start portion of the plot 1082 representing the period during which the patient 1070 is accelerating to his normal walking speed and excludes the end portion of the plot 1082 representing the period during which the patient is decelerating until he stops. Thus, it represents the period during which the patient is walking at a substantially constant speed.

[0175] Referring to FIGS. 4 and 9-12, the implantable control circuit 1032 may be configured to determine whether the patient 1070 is walking by comparing the acceleration signals and angular velocity signals generated by the accelerometer and gyroscope of the IMU 1022 with the benchmark normal walking signals shown, for example, in plots 1080, 1082, 1084, 1086. For example, the implantable control circuit 1032 may use the digital acceleration signals a x (t), a y (t), a z (t) and the digital angular velocity signals Ω x (t), Ω y (t), Ω z(t) is preferably configured to be correlated with each benchmark normal walking signal, and due to this correlation, when a correlation value greater than a correlation threshold having a value within an approximate range, for example, from 0.60 to 0.95 (1.0 is the maximum value that can cause a correlation), occurs, it is possible to determine whether patient 1070 is walking. As a modification, in order to save processing power and time, the implantable control circuit 1032 is preferably configured to correlate the ranges of the acceleration signal and the angular velocity signal generated by the accelerometer and gyroscope of the IMU 1022 with the region of the benchmark normal walking signal, for example, the heel strike range. And the determination of whether patient 1070 is walking is preferably one of one or more determinations in which the implantable control circuit 1032 is configured to determine whether the acceleration signal and the angular velocity signal from the IMU 1022 are limited signals that are storage targets in the configuration of the implantable control circuit 1032. Each benchmark normal walking signal can be generated, for example, by patient 1070 himself / herself in a doctor's clinic (the doctor can control the implantable control circuit 1032 to store the benchmark normal walking signal in the memory opening 1024). Alternatively, each benchmark normal walking signal can be generated by simulating the normal walking of patient 1070 or in response to a statistical analysis of the normal walking of other patients forming a group of the same or similar artificial knee joints. When each benchmark normal walking signal is generated in response to walking other than the actual walking of patient 1070 himself / herself, during the correlation, the implantable control circuit 1032 can expand or contract the benchmark normal walking signal in the dimension of time or amplitude so as to take into account the stride of patient 1070. For example, the taller patient 1070 is, the longer the patient's stride will be, and conversely, the shorter patient 1070 is, the shorter the patient's stride will be.

[0176] Still referring to FIGS. 9-12, modified embodiments of the above-described benchmark signal generation technique and signal comparison technique are envisioned. For example, the embodiments described in connection with FIGS. 3-8 and FIGS. 13-27 can be utilized for the signals and techniques described in connection with FIGS. 9-12.

[0177] FIG. 13 shows, according to one embodiment, while patient 1070 is walking forward in normal gait between one of the heel strikes described above in connection with FIGS. 9-12, the analog acceleration signals a x (t), a y (t), a z (t) generated by the accelerometer of IMU 1022 (FIG. 4) in response to the accelerations along the x-axis 1060, y-axis 1062, and z-axis 1064 (FIG. 6), respectively. In the above-described example, the x-axis, y-axis, and z-axis have the ideal alignment described in connection with FIGS. 7 and 8, artificial knee joint 1072 (FIGS. 7 and 8) has little or no degradation caused by instability or wear, and IMU 1022 samples each of the analog acceleration signals a x (t), a y (t), a z (t) at the same sample time, and the effective sample rate is 800 Hz. For example, with respect to the artificial knee joint, since the weight is transferred to the artificial joint during heel strike, it can be said that the heel strike region is a good region of the walking signal to be analyzed for instability and wear of the artificial knee joint.

[0178] FIG. 14 shows, according to one embodiment, the x-acceleration, y-acceleration, and z-acceleration each represented by the digitized version of the analog acceleration signals a x (t), a y (t), a z (t) in a plot 1092 representing the relationship between the spectral distributions X(f), Y(f), Z(f) and frequency. For example, a server (e.g., a cloud server) located far from the artificial knee joint receives the analog acceleration signals a x (t), a y (t), a zThe spectral distributions X(f), Y(f), and Z(f) can be generated by performing a discrete Fourier transform (DFT) or a fast Fourier transform (FFT) on each of the digitized versions of (t). Although described as having arbitrary units above, the spectral distributions X(f), Y(f), and Z(f) should be mathematically manipulated to have any suitable unit, for example, a unit of energy (joule, root mean square of joule squared).

[0179] FIG. 15 is a plot 1094 showing the relationship between the cumulative spectral distribution XYZ(f) (expressed, for example, in root mean square of joule squared, logarithmic scale units, or other arbitrary units different therefrom) of the x, y, and z accelerations represented by the digitized versions of the analog acceleration signals a x (t), a y (t), a z (t) and frequency. For example, a server located far from the artificial knee joint (e.g., a cloud server) can integrate each of the contents X(f), Y(f), and Z(f) (FIG. 14) with respect to time and sum the respective integration results to generate a cumulative spectral distribution.

[0180] Referring to FIGS. 13 to 15, the spectral distributions X(f), Y(f), and Z(f) and the cumulative spectral distribution XYZ(f) can be used as benchmarks for determining whether the artificial knee joint 1072 exhibits degradation caused by instability or wear. For example, according to the analysis results of the cumulative spectral distribution XYZ(f), for the artificial knee joint 1072 indicating no instability or degradation, approximately 90% of the RMS motion is in the frequency state below 10 Hz, and approximately 98% of the RMS motion is in the frequency state below 20 Hz. Therefore, if the cumulative spectral distribution XYZ(f) generates a relatively large RMS motion exceeding 20 Hz, it can be understood that the artificial knee joint 1072 seems to exhibit instability or degradation.

[0181] The respective benchmark analog acceleration signals a x (t), a y (t), a z (t) that generate the benchmark spectral distributions X(f), Y(f), Z(f) and the benchmark cumulative spectral distribution XYZ(f) can be generated, for example, by the patient 1070 himself / herself within a doctor's clinic (the doctor can control the implanted control circuit 1032 to store the benchmark normal walking, non-unstable and non-degraded signal in the memory opening 1024). Alternatively, each benchmark normal walking, non-unstable and non-degraded signal can be generated by simulating the normal walking of the patient 1070 or in response to a statistical analysis of the normal walking of other patients forming a group of the same or similar artificial knee joints. x (t), a y (t), a z (t) can be generated, for example, by the patient 1070 himself / herself within a doctor's clinic (the doctor can control the implanted control circuit 1032 to store the benchmark normal walking, non-unstable and non-degraded signal in the memory opening 1024). Alternatively, each benchmark normal walking, non-unstable and non-degraded signal can be generated by simulating the normal walking of the patient 1070 or in response to a statistical analysis of the normal walking of other patients forming a group of the same or similar artificial knee joints.

[0182] Still referring to FIGS. 13 - 15, modified embodiments of the above-described benchmark signal, spectral distribution, and cumulative spectral distribution generation techniques and analysis techniques are envisioned. For example, the sample rate and ODR that the IMU 1022 executes to generate the above-described benchmark signal may each be other than 3200 Hz and other than 800 Hz. Further, the embodiments described in connection with FIGS. 3 - 12 and FIGS. 16 - 27 can be utilized for the signals, spectral distributions, cumulative spectral distributions, and techniques described in connection with FIGS. 13 - 15.

[0183] FIG. 16 shows, according to one embodiment, that the accelerometers of the IMU 1022 (FIG. 4) generate analog acceleration signals a x (t), a y (t), a z (t) (unit is m / s x (t), a y (t), a z (t) in response to the accelerations along the x-axis 1060, y-axis 1062, and z-axis 1064 (FIG. 6) each time the heel strikes as described above in connection with FIGS. 9 - 12 while the patient 1070 (FIGS. 7 and 8) is walking forward during normal walking. 2It is a plot 1096 representing the relationship between the digitized version of and time. In the above-described embodiment, the x-axis, y-axis, and z-axis have the ideal alignment described in relation to FIGS. 7 and 8, and the artificial knee joint 1072 (FIGS. 7 and 8) shows instability but little or no wear-induced degradation. The IMU 1022 samples each of the analog acceleration signals a x (t), a y (t), a z (t) at a sample rate (which may be referred to as the "raw sample rate") of 3200 Hz, and the ODR (effective sample rate) is 800 Hz. In this case, "instability" means that the bending of the artificial knee joint 1072 (FIGS. 7 and 8) is not smooth while the patient 1070 is walking. That is, the artificial knee joint 1072 shows instability when the femoral component of the artificial knee joint vibrates along or around one or more of the x-axis 1060, y-axis 1062, and z-axis 1064 in an unintended or undesired manner different from that.

[0184] FIG. 17 is a plot 1098 representing the relationship between the respective spectral distributions X(f), Y(f), Z(f) (arbitrary units, e.g., joules, logarithmic scale) of the x, y, and z accelerations shown by the digitized versions of the analog acceleration signals a x (t), a y (t), a z (t) and frequency according to one embodiment. For example, a server located far from the artificial knee joint (e.g., a cloud server) can generate the spectral distributions X(f), Y(f), Z(f) by performing a discrete Fourier transform (DFT) or (fast Fourier transform (FFT)) on each of the digitized versions of the analog acceleration signals a x (t), a y (t), a z (t).

[0185] FIG. 18, according to one embodiment, shows the analog acceleration signals a of FIG. 16 x (t), a y (t), az A plot 1100 representing the relationship between the cumulative spectral distribution XYZ(f) (arbitrary units, e.g., joule root mean square, logarithmic scale) of x, y, and z accelerations represented by the digitized version of (t) and frequency. For example, a server (e.g., a cloud server) located far from the artificial knee joint 1072 (Figs. 7 and 8) can integrate each of the contents X(f), Y(f), Z(f) (Fig. 14) with respect to time and sum the respective integration results to generate a cumulative spectral distribution.

[0186] Referring to Figs. 16 - 18, according to the analysis results of the cumulative spectral distribution XYZ(f), for the artificial knee joint 1072 that shows instability but not degradation, approximately 90% of the RMS motion is in the frequency state below 28 Hz (compared to 10 Hz (Figs. 13 - 15) in the case of the artificial knee joint 1072 that does not show instability), and approximately 98% of the RMS motion is in the frequency state below 44 Hz (compared to 20 Hz (Figs. 13 - 15) in the case of the artificial knee joint 1072 that does not show instability). The frequency ranges at 90% and 98% of the RMS motion of the artificial knee joint 1072 are significantly wider than the corresponding benchmark frequency ranges of the RMS motion of the artificial knee joint that shows neither instability nor degradation, and may represent the artificial knee joint 1072 that shows at least one of instability and degradation (according to the trend shown by the initial experimental results, the RMS frequency motion frequency range resulting from the spectral distribution XYZ(f) plotted in Fig. 18 represents the instability of the artificial knee joint and not degradation).

[0187] To determine the magnitude, form, and other characteristics of the instability shown by the artificial knee joint 1072 (Figs. 7 and 8), for example, it is advisable to analyze one or more of the following parameters (e.g., automatically on a server remote from the artificial knee joint, e.g., on a cloud server). (1) The analog acceleration signal a in Fig. 16 x (t), a y (t), a z The magnitude, number, and relative phase of one or more peaks of the digitized version of (t) (2) the magnitude of each of one or more of the spectral distributions X(f), Y(f), Z(f) at each of one or more frequencies, and (3) the magnitude of the cumulative spectral distribution XYZ(f) at each of one or more frequencies.

[0188] As described elsewhere in this application, it may be beneficial to use one or more deterministic algorithms or one or more machine learning algorithms (e.g., neural networks) to characterize instability and suggest one or more procedures for correcting instability. For example, the algorithm may process one or more of the digitized versions of the analog acceleration signals a x (t), a y (t), a z (t) (FIG. 16), the spectral distributions X(f), Y(f), Z(f), and the cumulative spectral distribution XYZ(f) to determine the maximum (peak-to-peak) amplitude of instability (e.g., translation or rotation less than 2 millimeters (mm), translation or rotation between 2 and 3 millimeters (mm), and translation or rotation greater than 3 mm), the putative cause of the instability (e.g., too much "slop" between the femoral component and the spacer ("pack") with respect to the instability), and a procedure likely to correct the instability (e.g., resizing and replacing the pack, sending patient 1070 (FIGS. 7 and 8) to physical therapy to tighten the muscles, ligaments, and tendons associated with the artificial knee joint).

[0189] Still referring to FIGS. 16-18, modified embodiments of the above-described analysis and algorithms for detecting, quantifying, and proposing correction of instability of the artificial knee joint 1072 (FIGS. 7 and 8) are envisioned. For example, the above-described analysis and algorithms may be used, or modified for use with implantable prostheses other than artificial knee joints. Further, the embodiments described in connection with FIGS. 3-15 and FIGS. 19-27 are applicable to the analysis and algorithms described in connection with FIGS. 16-18.

[0190] FIG. 19 is a plot 1102 showing the relationship between time and the digitized versions of analog acceleration signals ax(t), ay(t), and az(t) (units m / s2) that are generated in response to acceleration along the x-axis 1060, y-axis 1062, and z-axis 1064 (FIG. 6) each time the heel strikes during normal walking of patient 1070 (FIGS. 7 and 8) as described above in connection with FIGS. 9-12. In the above-described example, the x-axis, y-axis, and z-axis have the ideal alignment described in connection with FIGS. 7 and 8, the artificial knee joint 1072 (FIGS. 7 and 8) exhibits instability and early onset wear-induced degradation, and the IMU 1022 samples each of the analog acceleration signals ax(t), ay(t), and az(t) at the same sample time, the sample rate is 3200 Hz, and the ODR is 800 Hz. In this case, "early onset degradation" means that the artificial knee joint 1072 has just begun to show signs of wear (e.g., rough engagement (grinding) of the femur component of the artificial knee joint with the plastic spacer) caused by repeated flexion of the knee joint. That is, the artificial knee joint 1072 exhibits wear when the femur component engages roughly with the plastic spacer, e.g., grinds it, while the patient 1070 (FIGS. 7 and 8) bends the artificial knee joint, e.g., during walking. x (t), a y (t), a z (t) (units are m / s 2 ) and time. In the above-described embodiment, the x-axis, y-axis, and z-axis have the ideal alignment described in connection with FIGS. 7 and 8, the artificial knee joint 1072 (FIGS. 7 and 8) exhibits instability and early onset wear-induced degradation, and the IMU 1022 samples each of the analog acceleration signals a x (t), a y (t), a z (t) at the same sample time, the sample rate is 3200 Hz, and the ODR is 800 Hz. In this case, "early onset degradation" means that the artificial knee joint 1072 has just begun to show signs of wear (e.g., rough engagement (grinding) of the femur component of the artificial knee joint with the plastic spacer) caused by repeated flexion of the knee joint. That is, the artificial knee joint 1072 exhibits wear when the femur component engages roughly with the plastic spacer, e.g., grinds it, while the patient 1070 (FIGS. 7 and 8) bends the artificial knee joint, e.g., during walking.

[0191] FIG. 20 is a plot 1104 showing the relationship between frequency and the spectral distributions X(f), Y(f), Z(f) (arbitrary units, e.g., joules, logarithmic scale) of the x, y, and z accelerations, respectively, as indicated by the digitized versions of the analog acceleration signals ax(t), ay(t), and az(t) of FIG. 19. For example, a server located far from the artificial knee joint (e.g., a cloud server) receives the analog acceleration signals a x (t), a y (t), a z (t). x (t), a y (t), a zThe spectral distributions X(f), Y(f), and Z(f) can be generated by performing the discrete Fourier transform (DFT) or the fast Fourier transform (FFT) on each of the digitized versions of (t).

[0192] FIG. 21 shows, according to one embodiment, the analog acceleration signals a x (t), a y (t), a z in FIG. 19. A plot 1106 representing the relationship between the cumulative spectral distribution XYZ(f) of the x, y, and z accelerations (arbitrary units, e.g., joule root mean square, logarithmic scale) represented by the digitized versions of (t) and the frequency. For example, a server located far from the artificial knee joint 1072 (FIGS. 7 and 8) (e.g., a cloud server) can integrate each of the spectral distributions X(f), Y(f), and Z(f) (FIG. 14) with respect to time and sum the respective integration results to generate a cumulative spectral density.

[0193] Referring to FIGS. 19 to 21, according to the analysis results of the cumulative spectral distribution XYZ(f), for the artificial knee joint 1072 showing instability and premature degradation, approximately 90% of the RMS motion is at frequencies below 34 Hz (10 Hz for an artificial knee joint showing neither instability nor degradation (FIGS. 13 to 15), and 28 Hz for an artificial knee joint showing instability but not degradation (FIGS. 16 to 18)), and approximately 98% of the RMS motion is at frequencies below 175 Hz (20 Hz for the artificial knee joint 1072 showing neither instability nor degradation (FIGS. 13 to 15), and 44 Hz for an artificial knee joint showing instability but not degradation (FIGS. 16 to 18)). The frequency ranges at 90% and 98% of the RMS motion of the artificial knee joint 1072 are significantly wider than the corresponding benchmark frequency ranges of the RMS motion of an artificial knee joint showing neither instability nor degradation, and the frequency range corresponding to the RMS motion of an artificial knee joint showing instability but not degradation may represent the artificial knee joint 1072 showing both instability and premature degradation.

[0194] To determine the magnitude, form, and other characteristics of the instability and degradation shown by the artificial knee joint 1072 (Figs. 7 and 8), for example, it may be good to analyze one or more of the following parameters (e.g., automatically on a server remote from the artificial knee joint, such as on a cloud server). (1) The magnitude, number, and relative phase of one or more peaks of the digitized version of the analog acceleration signal a x (t), a y (t), a z (t) shown in Fig. 19 (2) The magnitude of each of one or more of the spectral distributions X(f), Y(f), Z(f) at each of one or more frequencies shown in Fig. 20, and (3) The magnitude of each of the cumulative spectral distributions XYZ(f) at each of one or more frequencies shown in Fig. 21.

[0195] As described elsewhere in this application, it may be good to use one or more deterministic algorithms or one or more machine learning algorithms (e.g., neural networks) to characterize one or both of the instability and degradation and to suggest one or more procedures for correcting one or both of the instability and degradation. For example, the algorithm may be the analog acceleration signal a x (t), a y (t), a z(t) The digitized version of (FIG. 16), one or more of the spectral distributions X(f), Y(f), Z(f), and the cumulative spectral distribution XYZ(f) are processed to determine the maximum (peak-to-peak) amplitude of one or both of instability and degradation (e.g., translation or rotation less than 2 millimeters (mm), translation or rotation of 2 - 3 millimeters (mm), and translation or rotation greater than 3 mm), the putative cause of one or both of instability and degradation (e.g., too much "slop" between the femoral component and the spacer ("pack") regarding instability, wear of the pack or femoral component regarding degradation), and the procedure with a high likelihood of correcting one or both of instability and degradation (e.g., resizing and replacing the pack, sending patient 1070 (FIGS. 7 and 8) for physical therapy to tighten the muscles, ligaments, and tendons associated with the artificial knee joint).

[0196] Still referring to FIGS. 19 - 21, modified embodiments of the above-described analysis and algorithms for detecting, quantifying, and proposing corrections for instability of the artificial knee joint 1072 (FIGS. 7 and 8) are envisioned. For example, the above-described analysis and algorithms may be used, or they may be modified for use with implantable prostheses other than the artificial knee joint. Further, the embodiments described in connection with FIGS. 3 - 18 and FIGS. 22 - 27 are applicable to the analysis and algorithms described in connection with FIGS. 19 - 21.

[0197] FIG. 22, according to one embodiment, shows that the accelerometers of the IMU 1022 (FIG. 4) each generate an analog acceleration signal a x (t), a y (t), a z (t) (units are m / s 2A plot 1108 representing the relationship between the digitized version of and time. In the above-described embodiment, the x-axis, y-axis, and z-axis have the ideal alignment described in connection with FIGS. 7 and 8, and the artificial knee joint 1072 (FIGS. 7 and 8) shows a state of deterioration induced by instability and progressive wear. The IMU 1022 samples each of the analog acceleration signals a x (t), a y (t), a z (t) at a sample rate of 3200 Hz and an ODR of 800 Hz. In this case, "progressive deterioration" means that the artificial knee joint 1072 (FIGS. 7 and 8) clearly shows signs of wear caused by repeated flexion of the knee joint (e.g., rough engagement (grinding) between the femoral component of the artificial knee joint and the plastic spacer). That is, the artificial knee joint 1072 exhibits wear when the femoral component engages roughly with the plastic spacer while the patient 1070 (FIGS. 7 and 8) bends the artificial knee joint, for example, during walking, and grinds it, for example.

[0198] FIG. 23 is a plot 1110 representing the relationship between the respective spectral distributions X(f), Y(f), Z(f) (arbitrary units, e.g., joules, logarithmic scale) of the x, y, and z accelerations shown by the digitized versions of the analog acceleration signals a x (t), a y (t), a z (t) and frequency according to one embodiment. For example, a server located far from the artificial knee joint (e.g., a cloud server) can generate the spectral distributions X(f), Y(f), Z(f) by performing a discrete Fourier transform (DFT) or (fast Fourier transform (FFT)) on each of the digitized versions of the analog acceleration signals a x (t), a y (t), a z (t).

[0199] FIG. 24, according to one embodiment, shows the analog acceleration signals a of FIG. 22 x (t), a y (t), az A plot 1112 representing the relationship between the cumulative spectral distribution XYZ(f) (in arbitrary units, e.g., joule root mean square, logarithmic scale) of the x, y, and z accelerations represented by the digitized version of (t) and the frequency. For example, a server (e.g., a cloud server) located far from the artificial knee joint 1072 (Figs. 7 and 8) can integrate each of the contents X(f), Y(f), Z(f) (Fig. 14) with respect to time and sum the respective integration results to produce a cumulative spectral distribution.

[0200] Referring to Figs. 22 to 24, according to the analysis results of the cumulative spectral distribution XYZ(f), for the artificial knee joint 1072 showing instability and early degradation, approximately 90% of the RMS motion is at frequencies below 306 Hz (10 Hz for an artificial knee joint showing neither instability nor degradation (Figs. 13 to 15), 28 Hz for an artificial knee joint showing instability but not degradation (Figs. 16 to 18), and 34 Hz for an artificial knee joint showing both instability and early degradation), and approximately 98% of the RMS motion is at frequencies below 394 Hz (20 Hz for the artificial knee joint 1072 showing neither instability nor degradation (Figs. 13 to 15), 44 Hz for an artificial knee joint showing instability but not degradation (Figs. 16 to 18), and 175 Hz for an artificial knee joint showing both instability and early degradation). The frequency ranges at 90% and 98% of the RMS motion of the artificial knee joint 1072 are significantly wider than the corresponding benchmark frequency ranges of the RMS motion of an artificial knee joint showing neither instability nor degradation, and the frequency ranges corresponding to the RMS motion of artificial knee joints showing instability but not degradation and both instability and early degradation may represent the artificial knee joint 1072 showing both instability and advanced degradation.

[0201] To determine the magnitude, form, and other characteristics of the instability and degradation shown by the artificial knee joint 1072 (Figs. 7 and 8), for example, it is advisable to analyze one or more of the following parameters (e.g., automatically on a server remote from the artificial knee joint, e.g., on a cloud server). (1) The analog acceleration signal a in Fig. 22x (t), a y (t), a z The magnitude, number, and relative phase of one or more peaks among the digitized versions of (t) (2) The magnitude of each of one or more of the spectral distributions X(f), Y(f), Z(f) at each of one or more frequencies of FIG. 23, and (3) The magnitude of each of the cumulative spectral distributions XYZ(f) at each of one or more frequencies of FIG. 24.

[0202] As described elsewhere in this application, one or more deterministic algorithms or one or more machine learning algorithms (e.g., neural networks) may be used to characterize one or both of instability and degradation and to suggest one or more procedures for correcting one or both of instability and degradation. For example, the algorithm may process one or more of the digitized version of the analog acceleration signal a x (t), a y (t), a z (t) (FIG. 22), the spectral distributions X(f), Y(f), Z(f), and the cumulative spectral distribution XYZ(f) to determine the maximum (peak-to-peak) amplitude of one or both of instability and degradation (e.g., translation or rotation less than 2 millimeters (mm), translation or rotation of 2 - 3 millimeters (mm), and translation or rotation greater than 3 mm), the putative cause of one or both of instability and degradation (e.g., excessive "slop" between the femoral component and the spacer ("pack") for instability, wear of the pack and femoral component for degradation), and the procedure likely to correct one or both of instability and degradation (e.g., resizing and replacing the pack, sending patient 1070 (FIGS. 7 and 8) for physical therapy to tighten the muscles, ligaments, and tendons associated with the artificial knee joint).

[0203] Referring still to FIGS. 22 - 24, modified embodiments of the above-described analysis and algorithms for detecting, quantifying, and proposing corrections to the instability of the artificial knee joint 1072 (FIGS. 7 and 8) are envisioned. For example, the above-described analysis and algorithms may be used, or modified for use with implantable prostheses other than the artificial knee joint. Further, the algorithm may result in a digitalized version corresponding to one or more of the angular velocities Ω x (t), Ω y (t), Ω z (t) (units are ° / s). Further, the algorithm may result in a result corresponding to one or more portions of the patient's 1070 (FIGS. 7 and 8) walking other than or in addition to heel strike (e.g., toe off). Additionally, the embodiments described in connection with FIGS. 3 - 21 and FIGS. 25 - 27 are applicable to the analysis and algorithms described in connection with FIGS. 22 - 24.

[0204] FIG. 25 is a flow diagram 1120 of the operation of the implantable circuit 1010 of FIG. 4 according to one embodiment.

[0205] Referring to FIGS. 4 and 25, in step 1122, the implantable circuit 1010 detects the movement of the implanted prosthesis, such as the artificial knee joint 1072 of FIGS. 7 and 8. For example, the control circuit 1032 monitors the respective digitized output signals from one or more of the accelerometer and gyroscope of the IMU 1022, and detects the movement of the implanted prosthesis in response to the magnitude of one or more of the digitized output signals that exceed the movement detection threshold.

[0206] Next, in step 1124, in response to detecting the movement of the implanted prosthesis in step 1122, by the control circuit 1032, the IMU 1022 samples the analog signals output from one or both of the accelerometer and gyroscope of the IMU (hereinafter, it is assumed that the IMU 1022 samples the analog signals output from both the accelerometer and gyroscope of the IMU). The IMU 1022 samples the analog signals at the same sample rate or at respective sample rates. For example, the IMU 1022 samples the analog signals output from all of the x, y, and z accelerometers and gyroscopes at 1600 Hz (raw sample rate), and scales down the raw sample rate to achieve an effective sample rate of 800 Hz (also called the output data rate (ODR)) for each of the accelerometer and gyroscope signals. Further, by the control circuit 1032, the IMU 1022 samples the analog signals output from the accelerometer and gyroscope for a finite time period, for example, during a 10-second time window.

[0207] Next, in step 1126, control circuit 1032 determines whether the samples collected by IMU 1022 in step 1124 are of a limited event, such as whether patient 1070 (Figs. 7 and 8) is walking on implanted artificial knee joint 1072 (Figs. 7 and 8). For example, control circuit 1032 correlates samples from each of one or more of the accelerometer and gyroscope with benchmark samples corresponding to the limited event (e.g., samples stored in memory circuit 1024 of the figure), compares this correlation result with a threshold value, and if the correlation result is equal to or exceeds the threshold value, determines that the sample is of the limited event, or if the correlation result is less than the threshold value, determines that the sample is not of the limited event. Alternatively, control circuit 1032 can make a less complex and less energy-consuming determination by determining that a sample is a limited event even if the sample had peak-to-peak amplitudes and durations that would indicate that the patient was walking for a threshold length of time. The determination of whether samples were actually collected while the patient was walking can be performed by a remote destination (e.g., a cloud server). For example, control circuit 1032 is configured to sample analog signals output by one or both of the accelerometer and gyroscope in response to detected patient movement three times a day at a relatively high sample rate (e.g., 3200 Hz) and ODR (e.g., 800 Hz) by IMU 1022, and statistically, if at least one of the detected movements is that the patient is walking for at least a threshold length of time, this technique consumes less energy from battery 1012 than the energy consumed by the IMU while providing appropriate prosthesis information and samples fewer events, but can determine that the movement corresponding to the sampled event is the patient's walking.

[0208] If control circuit 1032 determines that the samples collected by IMU 1022 in step 1124 are not of a limited event, the control circuit returns to step 1122.

[0209] However, if the control circuit 1032 determines that the samples collected by the IMU 1022 at step 1124 are those of a limited event, the control circuit proceeds to step 1128, during which the control circuit causes the memory circuit 1024 to store the sample itself and the respective sample information for each set of samples. A set of samples includes samples from each of the accelerometer and gyroscope, and the sample information includes, for example, what the accelerometer or gyroscope that generated the analog signal from which the set of samples was collected is, the raw sample rate and ODR, the start time of the sample set (the collection time of the first sample of the set), the end time of the sample set (the collection time of the last sample of the set), the length of the sample window, and the dynamic amplitude input range and amplitude output range of the ADC that collected the samples. The dynamic amplitude input range is the maximum peak, i.e., the peak-to-peak signal amplitude that the ADC can receive without "cutting off" the input signal. And the amplitude output range is the maximum peak, or peak-to-peak, i.e., the maximum range that the samples span, and this amplitude output range is an indicator of the analog amplitude represented by each digital sample. If the sample information (e.g., raw sample rate, ODR, sample window) is the same for each sample from each accelerometer and gyroscope, the control circuit 1032 may group all of the accelerometer and gyroscope samples collected during the same time window into a single set of samples with common sample information.

[0210] Next, at step 1130, the control circuit 1032 generates a respective message for each stored set of samples and corresponding sample information, the message including a header and a payload. The header includes the sample information, and the payload includes the samples forming the set. The header may further include additional information, such as a unique identifier of the implantable prosthesis (e.g., serial number), a unique identifier of the patient 1070 (Figs. 7 and 8), and the length of the payload.

[0211] Next, in optional step 1132, control circuit 1032 encrypts some or all of each message, for example, as may be specified by HIPAA. As part of this step or step 1130, control circuit 1032 may include in the message header a public encryption key that allows the recognized beneficiary of the message to decrypt the encrypted portion of the message. Alternatively, control circuit 1032 may not encrypt the sample message, or may not perform any encryption on the sample message until it is sent to the remote destination.

[0212] Next, in step 1134, control circuit 1032 stores each encrypted or unencrypted message in memory 1024.

[0213] Next, in step 1136, control circuit 1032 determines whether base station 1004 (FIG. 3) has polled implantable circuit 1010 for all messages generated since the last time implantable circuit 1010 sent a message to base station 1004 (FIG. 3).

[0214] If control circuit 1032 determines that base station 1004 (FIG. 3) has not polled implantable circuit 1010, the control circuit takes no further action regarding the message and effectively waits for the base station to poll the implantable circuit.

[0215] However, if control circuit 1032 determines that base station 1004 (FIG. 3) has polled implantable circuit 1010, the control circuit proceeds to step 1138.

[0216] In step 1138, control circuit 1032 generates one or more data packets that collectively contain the messages stored in memory 1024 as described above in connection with step 1134. Control circuit 1032 generates one or more data packets in accordance with any suitable communication protocol, and each data packet includes a header and a payload. The header includes information such as, for example, an identifier unique to the implanted prosthesis (e.g., serial number), an identifier unique to patient 1070 (Figs. 7 and 8), and a sequence number indicating the relative position within the sequence of data packets that control circuit 1032 sends to base station 1004 (Fig. 4) (the information in the data packet header may be redundant with respect to some or all of the information in the message header). And the payload includes one or more (all or part) of the messages stored in memory circuit 1024. For example, if the stored message is too long to be a single data packet, control circuit 1032 may split this message into two or more data packets (therefore, the destination of the message can reconstruct the message based on the sequence number). In contrast, if the stored message is not long enough to fill the payload of a data packet, the data packet may include one or more other entire messages or parts thereof in addition to this message. Further, instead of including a message header, the data packet payload may include only the message payload (sample), and the contents of the message header may be merged with the data packet header or included in it in a different way.

[0217] Next, in optional step 1140, control circuit 1032 encrypts at least the prosthesis and patient identifier, such as can be specified by HIPAA, for some or all of each data packet. As part of this step or part of step 1140, control circuit 1032 may include within the data packet header a public encryption key such that the recognized beneficiary of the message can decrypt the encrypted portion of the data packet header. If some or all of the message was encrypted in step 1132, control circuit 1032 may decrypt the message before creating the data packet. In a variant, control circuit 1032 may maintain the message in encrypted form, such that at least a portion of the encrypted portion of the message is double encrypted (message level encryption and data packet level encryption). In another variant, control circuit 1032 may not encrypt the prosthesis identifier, such that base station 1004 or smart device 1005 (FIG. 3) can use the prosthesis identifier to determine whether the base station or smart device should ignore the data packet or receive and process the data packet.

[0218] Next, in step 1142, control circuit 1032 error codes one or more data packets, whether encrypted or not, in accordance with any suitable error coding technique (a communication protocol compatible with the one or more data packets can specify the error coding technique). By error coding one or more data packets, the destination can recover data packets containing errors introduced during propagation of the data packets from control circuit 1032 to the destination.

[0219] Next, in step 1144, the control circuit 1032 sends one or more error-encoded data packets to the base station 1004 (FIG. 3) via the RF transceiver 1025, the filter 1028, and the antenna 1030. As a variant, the control circuit 1032 sends one or more error-encoded data packets to the base station 1004 via the smart device 1005, sends them directly to the smart device 1005, or sends them to the smart device via the base station.

[0220] Next, in step 1146, the control circuit 1032 determines whether it is time to collect samples of another limited event.

[0221] When it is determined by the control circuit 1032 that it is not yet time to collect samples of another limited event, the implanted circuit 1010 enters the sleep mode or another power mode by the control circuit at step 1148 to conserve the power of the battery 1012 and extend its life. For example, the control circuit 1032 may open the switches 1016, 1018 to cut off the power to the IMU 1022 and the memory circuit 1024 respectively. Further, the clock and power management circuit 1020 includes a timer that notifies the control circuit 1032 to "wake up" the implanted circuit 1010 at a programmed absolute time or after a programmed length of time (e.g., one day, two days, one week, one month) has elapsed. In addition, it is advisable to associate the time between limited events with, for example, how much time has passed since the prosthesis was implanted in the patient 1070 (Figs. 7 and 8), or with health insurance billing codes, such as telemedicine codes or CPT codes. Regarding the former, for example, during the first three months (0 - 3 months) after implantation, the control circuit 1032 is configured to measure at least one limited event (e.g., walking at least 10 steps) every day, so that the patient's attending physician can monitor the functioning state of the implant. Next, during the 3 - 6 months after implantation, the control circuit 1032 may be configured to measure at least one limited event once a day, for example, after at least 24 hours of standby time, or every three days, for example, after at least 48 hours of standby time. During the 6 - 12 months, the control circuit 1032 may be configured to measure at least one limited event at least once a week, and then at least once or twice a month. Regarding the latter (health insurance billing codes), telemedicine codes or CPT codes are insurance codes for physicians to report patient information remotely, for example, via the Internet, by email, or by phone, to bill the insurance company. An example of such information is the analysis results performed on samples of one or more limited events detected and sampled by the IMU 1022 (Fig. 4).In insurance plans, generally, the maximum payment amount (e.g., $3,000 per year) that a physician can receive based on a telemedicine code or CPT code for a medical problem (e.g., artificial knee joint), and the frequency at which the physician is required to verify patient information to be eligible for the maximum payment amount are specified. As a result, the control circuit 1032 or other parts of the implantable circuit 1010 (e.g., the clock and power management circuit 1020) may be configured to detect and measure limited events related to the prosthesis at a frequency at which the patient's primary care physician is eligible for payments that the primary care physician can receive from the insurance company based on one or more telemedicine codes, CPT codes, or other reimbursement agreements. For example, if the insurance plan requires the physician to report the results of analyzing samples generated by the IMU 1022 daily for the first 0 to 6 months after implantation, weekly for the 6 to 12 months after implantation, and then monthly thereafter, the control circuit 1032 or other parts of the implantable circuit 1010 may be configured to detect at least one limited event per day for the first 0 to 6 months, at least one limited event per week for the 6 to 12 months after implantation, and at least one limited event per month thereafter, sample these events, and store these samples. As a variant, the control circuit 1032 or other parts of the implantable circuit 1010 may be configured to detect at least one limited event per day for at least 16 days per month, sample these events, and store these samples.

[0222] However, if it is determined by the control circuit 1032 in step 1146 that it is time to collect samples of another limited event, the control circuit returns to step 1122.

[0223] Still referring to FIG. 25, alternative embodiments of the operation of the implantable circuit 1010 are envisioned. For example, one or more of the steps in the flowchart 1120 may be omitted, or one or more steps may be added. Additionally, the embodiments described in connection with FIGS. 3 - 24 and FIGS. 26 and 27 may be utilized for the operation of the implantable circuit 1010.

[0224] Figure 26 is a flowchart 1160 of the operation of the base station circuit 1040 of FIG. 5 according to an embodiment.

[0225] Referring to FIGS. 5 and 26, at step 1162, the base station circuit 1040 polls the implantable circuit 1010 (FIG. 4) for data packets including the kinematic movement message (if any) generated by the implantable circuit since the last time the implantable circuit 1010 sent a data packet to the base station 1004 (FIG. 3).

[0226] Next, at step 1164, the base station circuit 1040 determines whether it has received a valid response to the poll from the implantable circuit 1010 of the prosthesis (e.g., the artificial knee joint 1072 of FIGS. 7 and 8) in which this base station circuit is implanted. For example, the base station circuit 1040 determines whether it has received a valid response from the implanted prosthesis by comparing the implant identifier in the valid response of this base station circuit with the version of the implant identifier stored in the memory circuit 1056 of the base station to determine whether this implant is registered with the base station 1004. If the implant identifier in the response is encrypted, the base station circuit 1040 decrypts this response and then determines whether the implant identifier is registered with the base station 1004 and is valid.

[0227] If it is determined by the base station circuit 1040 that this base station circuit has not yet received a valid polling response from the implantable circuit 1010 (FIG. 4), at step 1166, the control circuit 1058 determines whether the number of unsuccessful polling attempts during the current polling period exceeds a first threshold, i.e., Threshold_1.

[0228] In step 1166, if the control circuit 1058 determines that the number of unsuccessful polling attempts does not exceed Threshold_1, the control circuit returns to step 1162, polls the implanted type circuit 1010 of the implanted prosthesis again, and the control circuit may wait for the programmed delay time and then repoll the implanted type circuit. For example, Threshold_1 may have a value in the approximate range from 1 to 100.

[0229] However, in step 1166, if the control circuit 1058 determines that the number of unsuccessful polling attempts exceeds Threshold_1, the control circuit proceeds to step 1168.

[0230] In step 1168, the control circuit 1058 sends an error message via the RF transceiver 1054, the filter 1050, and the antenna 1046 to a destination, such as the cloud or another server. In this case, the error message indicates that the implanted prosthesis does not respond to the base station polling. As described in another place of this application, the destination can take appropriate measures, for example, check by e-mail or text to inform the patient 1070 (Figs. 7 and 8) that the power of the base station 1004 (Fig. 3) is "on" and is properly linked to the patient's home network 1006 (Fig. 3).

[0231] Referring to step 1164 again, if the control circuit 1058 determines that this control circuit has received a valid response to its polling of the implanted type circuit 1010 in Fig. 4, the control circuit proceeds to step 1170.

[0232] In step 1170, control circuit 1058 receives, from implantable circuit 1010 (FIG. 4) of the implantable prosthesis via antenna 1044, filter 1048, and RF transceiver 1052, data packets including samples and related information collected by IMU 1022 (FIG. 4). Control circuit 1058 also decodes and interprets (if necessary) the data packets, and analyzes the IMU samples and related information (e.g., unique prosthesis identifier, unique patient identifier).

[0233] In step 1172, control circuit 1058 determines whether the patient identifier, prosthesis identifier, and data parsed from the data packets received in step 1170 are correct (if the control circuit 1058 has already determined that the prosthesis identifier is correct in step 1164, the control circuit may refrain from re-determining whether the prosthesis identifier is correct). For example, control circuit 1058 error-decodes the data packets using an appropriate error decoding algorithm (e.g., cyclic redundancy check (CRC), Reed-Solomon) corresponding to the error encoding algorithm used by control circuit 1032 (FIG. 4), and determines whether the data packets contain irreparable errors corresponding to the decoding results. If control circuit 1058 determines that the data packets do not contain irreparable errors, control circuit 1058 compares the received patient identifier and prosthesis identifier with their respective identifiers stored in memory circuit 1056 or downloaded from a remote location. If control circuit 1058 determines that the data packets contain irreparable errors or that at least one of the received patient identifier and prosthesis identifier is incorrect, the control circuit proceeds to step 1174; otherwise, control circuit 1058 notifies implantable circuit 1010 of the receipt of valid data packets (e.g., in accordance with an appropriate handshake protocol), and proceeds to step 1176.

[0234] In step 1174, the base station control circuit 1058 determines whether the number of error-containing data packets (e.g., data packets including irreparable errors, inaccurate patient identifiers, or inaccurate prosthesis identifiers) received by this base station control circuit during the current polling cycle exceeds a second threshold Threshold_2. When it is found by the control circuit 1058 that the number of error-containing data packets received during the current polling cycle does not exceed Threshold_2, the control circuit returns to step 1162 and re-polls the implantable circuit 1010 (FIG. 4) of the prosthesis to re-send the data packet determined by the control circuit 1058 to have an error when received at the base station 1004 (FIG. 3). However, if the control circuit 1058 determines that the number of error-containing data packets received during the current polling cycle exceeds Threshold_2, the control circuit proceeds to step 1168 and sends an error message as described above.

[0235] In step 1172, if the base station control circuit 1058 determines that the patient identifier and the prosthesis identifier are accurate, then in step 1176, the control circuit generates a base station data packet that includes the analyzed message from the implanted circuit 1010 (FIG. 4) of the implanted prosthesis and that conforms to any suitable communication protocol. That is, the control circuit 1058 effectively repackages the message into one or more base station data packets. Each respective header of each base station data packet may include additional information, such as packet source (e.g., home network 1006 (FIG. 3)) and packet destination (e.g., cloud server) Internet or other address base station data packet routing information, in addition to some or all of the message header received from the prosthesis and the information in the prosthesis data packet. And each respective payload of each data packet includes accelerometer or gyroscope samples collected by the IMU 1022 (FIG. 4). Further, if the message is too long to be a single data packet, the control circuit 1058 may split this message into two or more data packets (so that the destination of the message can reconstruct the message by the sequence number). In contrast, if the message is not long enough to fill the payload of a data packet, the data packet may include, in addition to this message, one or more other entire messages or portions thereof. Further, rather than including a message header, the data packet payload may include only the message payload (samples), the contents of the message header may be merged with the data packet header, or included in this in a different way.

[0236] Next, in step 1178, the base station control circuit 1058 encrypts some or all of each base station data packet such that, for example, it can be specified by one or both of HIPAA and the communication protocol as the means for the control circuit to send the base station data packet. As part of this step or step 1176, the control circuit 1058 may include a public key within the data packet header such that the authorized beneficiary of the data packet can decrypt the encrypted portion of the data packet. If some or all of the message or prosthesis data packet is encrypted, the control circuit 1058 may decrypt the message before creating the base station data packet. In a variant, the control circuit 1058 may maintain the message and prosthesis data packet in encrypted form, such that at least a portion of the encrypted portion of the base station data packet is double or triple encrypted (encryption at two or more message levels, prosthesis data packet level encryption, and base station data packet level encryption).

[0237] Next, in step 1180, the control circuit 1058 error-codes one or more encrypted base station data packets in accordance with any suitable error coding technique (a communication protocol compatible with one or more base station data packets can specify the error coding technique). By error-coding one or more base station data packets, the destination can recover data packets containing errors introduced during the propagation of the data packets from the base station control circuit 1058 (FIG. 5) to the destination.

[0238] Next, in step 1182, the base station control circuit 1058 sends the one or more error-coded base station data packets via the RF transceiver 1054, filter 1050, antenna 1046, home network 1006 (FIG. 3), and the Internet or other communication network to a destination (e.g., a cloud server).

[0239] Next, the base station control circuit 1058 returns to step 1162, waits for a programmed time (e.g., one day, two to six days, one week, one month), and then polls the implanted prosthesis again after the programmed time has elapsed.

[0240] Still referring to FIG. 26, a modified embodiment of the operation of the base station circuit 1040 is envisioned. For example, the smart device 1005 (FIG. 3) may operate in a manner similar to that described above in connection with the flowchart 1160. Further, the smart base station circuit 1040 may perform one or more of the steps in the flowchart 1160, and the smart device 1005 may perform one or more of the remaining steps in the flowchart 1160. Further, as described above, the base station circuit 1040 may communicate with the implanted circuit 1010 (FIG. 4) via the smart device 1005, or the smart device may communicate with the implanted circuit via the base station circuit. Additionally, one or more of the steps in the flowchart 1160 may be omitted, and one or more additional steps may be added. Further, the embodiments described in connection with FIGS. 3-25 and 27 may be utilized for the operation of the base station circuit 1040.

[0241] FIG. 27 is a flowchart 1190 of the operation of the fuse 1014 and the control circuit 1032 of FIG. 4 according to one embodiment.

[0242] Referring to FIGS. 4 and 27, at step 1192, the fuse 1014 is electrically closed, and the control circuit 1032 determines whether the current from the battery 1012 through this fuse exceeds a first overcurrent threshold. For example, the control circuit 1032 or another part of the implanted circuit 1010 makes this determination by comparing the current through the fuse 1014 with a reference representing the overcurrent threshold.

[0243] If the control circuit 1032 determines that the current through the fuse 1014 exceeds the overcurrent threshold, the control circuit proceeds to step 1194; otherwise, the control circuit proceeds to step 1196.

[0244] In step 1194, the control circuit 1032 electrically opens the fuse 1014, increments the count value, and executes a delay, and then determines whether to close the fuse again. To enable the fuse 1014 to be opened or re-closed, the connection between the battery 1012 and the control circuit 1032 bypasses the fuse, so that opening the fuse does not cut off the power supply to the control circuit, or the control circuit has or is coupled to another power source (e.g., a battery) that supplies power to the control circuit even while the fuse 1014 is in the open state.

[0245] In step 1196, the control circuit 1032 determines whether the current from the battery 1012 through the fuse 1014 exceeds a second overcurrent threshold over a first threshold time length, where the second overcurrent threshold is smaller than the first overcurrent threshold. For example, the control circuit 1032 or another part of the implantable circuit 1010 makes this determination by comparing the current through the fuse 1014 with a reference representing the second overcurrent threshold and determining the length of time the current is greater than the second overcurrent threshold.

[0246] If it is determined by the control circuit 1032 that the current through the fuse 1014 exceeds the second overcurrent threshold over this first threshold time length, the control circuit proceeds to step 1194 and opens the fuse at least temporarily as described above; otherwise, the control circuit proceeds to step 1198.

[0247] In step 1198, the control circuit 1032 determines whether the voltage across the closed fuse 1014 exceeds a first overvoltage threshold. For example, the control circuit 1032 or another part of the implantable circuit 1010 makes this determination by comparing the voltage across the fuse 1014 with a reference representing the overvoltage threshold.

[0248] When the control circuit 1032 determines that the voltage across the fuse 1014 exceeds the overvoltage threshold, the control circuit proceeds to step 1194; otherwise, the control circuit proceeds to step 1200.

[0249] In step 1194, the control circuit 1032 electrically isolates the fuse 1014 at least temporarily as described above.

[0250] In step 1200, if the control circuit 1032 determines that the voltage across the fuse 1014 exceeds the second overvoltage threshold over a second threshold time length, for example, another part of the control circuit 1032 or the implantable circuit 1010 makes this determination by comparing the voltage across the fuse 1014 with a reference representing the second overvoltage threshold and determining the length of time the voltage is greater than the second overvoltage threshold.

[0251] If the control circuit 1032 determines that the voltage across the fuse 1014 exceeds the second overvoltage threshold over a second threshold time length, the control circuit proceeds to step 1194 to isolate the fuse at least temporarily as described above; otherwise, the control circuit proceeds to step 1202.

[0252] In step 1202, the control circuit 1032 determines whether the temperature of the closed fuse 1014 (or the temperature of another part of the prosthesis) exceeds a first over-temperature threshold. For example, another part of the control circuit 1032 or the implantable circuit 1010 makes this determination by comparing this temperature with a reference representing the over-temperature threshold.

[0253] If the control circuit 1032 determines that this temperature exceeds the over-temperature threshold, the control circuit proceeds to step 1194; otherwise, the control circuit proceeds to step 1204.

[0254] In step 1194, the control circuit 1032 electrically disconnects the fuse 1014 at least temporarily as described above.

[0255] In step 1204, if the control circuit 1032 determines that the temperature of the fuse 1014 (or the temperature of another part of the prosthesis) has exceeded a second over-temperature threshold for a third threshold time length, the second over-temperature threshold is lower than the first over-temperature threshold. For example, the control circuit 1032 or another part of the implantable circuit 1010 makes this determination by comparing this temperature with a reference signal representing the second over-temperature threshold and by determining the length of time the temperature is higher than the second over-temperature threshold.

[0256] If the control circuit 1032 determines that this temperature has exceeded the second over-temperature threshold for a third threshold time length, the control circuit proceeds to step 1194 to at least temporarily disconnect the fuse as described above; otherwise, the control circuit proceeds to step 1206.

[0257] In step 1206, the control circuit 1032 maintains the fuse 1014 in an electrically closed state and returns to step 1192.

[0258] However, if the control circuit 1032 proceeds to step 1194 from any of steps 1192 - 1204, the control circuit proceeds to step 1208.

[0259] In step 1208, the control circuit 1032 determines whether the count has exceeded a count threshold (the count represents the number of times the control circuit has disconnected the fuse 1014 since the battery 1012 started supplying power to the implantable circuit 1010). If the control circuit 1032 determines that this count has exceeded the count threshold, the control circuit proceeds to step 1210; otherwise, the control circuit proceeds to step 1212.

[0260] In step 1210, the control circuit 1032 permanently opens the fuse 1014. And if the prosthesis has a power source other than the battery 1012 for supplying power to the implanted circuit 1010 even when the fuse 1014 is in the open state, the control circuit 1032 generates an error message and one or more data packets including the error message, stores the one or more data packets in the memory circuit 1024, and in response to the next polling request from the base station, transmits the one or more data packets to the base station 1004 (Figure 3) via the RF transceiver 1026, the filter 1028, and the antenna 1030.

[0261] In step 1212, the control circuit 1032 determines whether a delay has elapsed. If the delay has not elapsed, the control circuit 1032 effectively waits until the delay elapses. However, if the delay has elapsed, the control circuit 1032 proceeds to step 1214.

[0262] In step 1214, the control circuit 1032 closes the fuse 1014 and returns to step 1192. By steps 1212 and 1214, the control circuit 1032 can reset the fuse 1014 because the event that the control circuit 1032 opened the fuse in step 1194 may be temporary and thus the fuse does not need to be permanently opened.

[0263] Still referring to FIGS. 4 and 27, a modified embodiment of the associated operation of fuse 1014 and implanted circuit 1010 is envisioned. For example, fuse 1014 may be a one-time openable fuse that is not controllable by control circuit 1032 and remains open once opened. Further, fuse 1014 may open in response to a number or just one of the states described in connection with steps 1192-1204 that does not reach all of them. For example, fuse 1014 may open only in response to current through the fuse exceeding an overcurrent threshold at step 1192. Further, one or more of the steps of flowchart 1190 may be omitted, and one or more additional steps may be added. Additionally, the embodiments described in connection with FIGS. 3-26 are applicable to the associated operation of fuse 1014 and implanted circuit 1010.

[0264] The following are exemplary embodiments of the present invention. 〔Embodiment Item 1〕 An implantable medical device, a. A circuit configured to be fixedly attached to an implantable artificial device, b. A power component, c. An apparatus configured to disconnect the circuit from the power component, the implantable medical device having the same. 〔Embodiment Item 2〕 The implantable medical device according to Embodiment Item 1, wherein the circuit includes an implantable report processor. 〔Embodiment Item 3〕 The implantable medical device according to Embodiment Item 1, wherein the power component includes a battery. 〔Embodiment Item 4〕 The implantable medical device according to Embodiment Item 1, wherein the device includes a fuse. 〔Embodiment Item 5〕 The implantable medical device according to Embodiment Item 1, wherein the device includes a resettable fuse. 〔Embodiment Item 6〕 The device is an implantable medical device according to Embodiment Item 1, including a switch. 〔Embodiment Item 7〕 The device is an implantable medical device according to Embodiment Item 1, including a one-time separable fuse. 〔Embodiment Item 8〕 The device is an implantable medical device according to Embodiment Item 1, configured to disconnect the circuit from the power component in response to a current passing through the device that exceeds a threshold current. 〔Embodiment Item 9〕 The device is an implantable medical device according to Embodiment Item 1, configured to disconnect the circuit from the power component in response to a voltage applied to the device that exceeds a threshold voltage. 〔Embodiment Item 10〕 The device is an implantable medical device according to Embodiment Item 1, configured to disconnect the circuit from the power component in response to a temperature that exceeds a threshold temperature. 〔Embodiment Item 11〕 The device is an implantable medical device according to Embodiment Item 1, configured to disconnect the circuit from the power component in response to a temperature of the circuit that exceeds a threshold temperature. 〔Embodiment Item 12〕 The device is an implantable medical device according to Embodiment Item 1, configured to disconnect the circuit from the power component in response to a temperature of the power component that exceeds a threshold temperature. 〔Embodiment Item 13〕 The device is an implantable medical device according to Embodiment Item 1, configured to disconnect the circuit from the power component in response to a temperature of the device that exceeds a threshold temperature. 〔Embodiment Item 14〕 The device is an implantable medical device according to Embodiment Item 1, configured to disconnect the circuit from the power component in response to a current passing through the device that exceeds a threshold current for at least a threshold time. 〔Embodiment Item 15〕 The device according to embodiment item 1, wherein the device is configured to disconnect the circuit from the power component in response to a voltage applied to the device that exceeds a threshold voltage for at least a threshold time. 〔Embodiment item 16〕 The device according to embodiment item 1, wherein the device is configured to disconnect the circuit from the power component in response to a temperature that exceeds a threshold temperature for at least a threshold time. 〔Embodiment item 17〕 The device according to embodiment item 1, wherein the device is configured to disconnect the circuit from the power component in response to a temperature of the circuit that exceeds a threshold temperature for at least a threshold time. 〔Embodiment item 18〕 The device according to embodiment item 1, wherein the device is configured to disconnect the circuit from the power component in response to a temperature of the power component that exceeds a threshold temperature for at least a threshold time. 〔Embodiment item 19〕 The device according to embodiment item 1, wherein the device is configured to disconnect the circuit from the power component in response to a temperature of the device that exceeds a threshold temperature. 〔Embodiment item 20〕 The device according to embodiment item 1, further comprising at least one mechanical component configured to function while the circuit is disconnected from the power component. 〔Embodiment item 21〕 An implantable medical device, a. a circuit configured to be fixedly attached to an implantable artificial device; b. a battery; c. a fuse coupled between the circuit and the battery. 〔Embodiment item 22〕 A method comprising the step of electrically opening a fuse disposed between a circuit and a battery, wherein at least the fuse and the circuit are provided in an implantable artificial device. [Embodiment Item 23] The method according to Embodiment Item 22, further comprising the step of operating at least one mechanical component of the implanted artificial device while the fuse is electrically open. [Embodiment Item 24] The method according to Embodiment Item 22, wherein the battery is provided in the implanted artificial device. [Embodiment Item 25] An implantable medical device, a. at least one sensor configured to generate a sensor signal; b. a control circuit configured to generate the sensor signal at a frequency associated with a telemedicine code for the at least one sensor. [Embodiment Item 26] An implantable medical device, a. at least one sensor configured to generate a sensor signal; b. a control circuit configured to generate the sensor signal at a frequency that enables a physician to be eligible for payment for the at least one sensor under a telemedicine insurance code. [Embodiment Item 27] An implantable medical device, a. at least one sensor configured to generate a sensor signal; b. a control circuit configured to generate the sensor signal at a frequency that enables a physician to be eligible for full payment for the at least one sensor under a telemedicine insurance code. [Embodiment Item 28] A method comprising the step of generating a sensor signal associated with an implantable medical device at a frequency such that a physician can be eligible for payment under a telemedicine insurance code. 〔Embodiment Item 29〕 A method comprising the step of generating a sensor signal associated with an implantable medical device at a frequency such that a physician can be eligible for full payment under a telemedicine insurance code. 〔Embodiment Item 30〕 An implantable prosthesis, a. A housing, b. An implantable circuit disposed within the housing, and the implantable circuit i. Generates at least one first signal representing movement, ii. Determines whether the signal meets at least one first criterion, and iii. Is configured to send the signal to a remote location in response to a determination that the signal meets the at least one first criterion. 〔Embodiment Item 31〕 The implantable prosthesis according to Embodiment Item 30, wherein the housing has a tibial extension. 〔Embodiment Item 32〕 The implantable prosthesis according to Embodiment Item 30, wherein the movement includes the movement of the patient. 〔Embodiment Item 33〕 The implantable prosthesis according to Embodiment Item 30, wherein the movement includes the patient's walking. 〔Embodiment Item 34〕 The implantable prosthesis according to Embodiment Item 30, wherein the at least one first criterion includes that the signal represents the movement for at least a threshold duration. 〔Embodiment Item 35〕 The implantable prosthesis according to Embodiment Item 30, wherein the at least one first criterion includes that the signal represents the movement for at least a threshold number of events. 〔Embodiment Item 36〕 a. The movement includes the patient's walking, b. The at least one first criterion includes that the signal represents the movement over at least a threshold number of walking times made by the patient, the implantable prosthesis according to embodiment item 30. 〔Embodiment item 37〕 The implantable circuit further, a. determines whether the movement meets at least one second criterion before determining whether the signal meets the at least one first criterion, b. is configured to determine whether the signal meets the at least one first criterion in response to the determination that the movement meets the second criterion, the implantable prosthesis according to embodiment item 30. 〔Embodiment item 38〕 The at least one second criterion includes that the movement is the patient's walking, the implantable prosthesis according to embodiment item 37. 〔Embodiment item 39〕 The implantable circuit further, a. determines whether the movement meets at least one second criterion before determining whether the signal meets the at least one first criterion in response to the signal, b. is configured to determine whether the signal meets the at least one first criterion in response to the determination that the movement meets the second criterion, the implantable prosthesis according to embodiment item 30. 〔Embodiment item 40〕 The implantable circuit further, a. determines whether the movement meets at least one second criterion in response to the signal, b. is configured to stop the generation of the signal in response to the determination that the movement does not meet the at least one second criterion, the implantable prosthesis according to embodiment item 30. 〔Embodiment item 41〕 The implantable circuit further, a. Determine whether the movement meets at least one second criterion in response to the signal; b. The implantable prosthesis according to embodiment item 30, configured to stop generating the signal before determining whether the signal meets at least one first criterion in response to a determination that the movement does not meet the at least one second criterion. [Embodiment item 42] The implantable circuit further a. Stores the signal in response to a determination that the signal meets at least one first criterion; b. The implantable prosthesis according to embodiment item 30, configured to send the stored signal to the remote location. [Embodiment item 43] The implantable prosthesis according to embodiment item 30, wherein the implantable circuit is further configured to encrypt the signal before sending the signal to the remote location. [Embodiment item 44] The implantable prosthesis according to embodiment item 30, wherein the implantable circuit is further configured to encode the signal before sending the signal to the remote location. [Embodiment item 45] The implantable circuit further a. Is configured to create a message including the signal; b. Sending the signal includes sending the message. The implantable prosthesis according to embodiment item 30. [Embodiment item 46] The implantable circuit further a. Is configured to generate a data packet including the signal; b. Sending the message includes sending the data packet to the remote location. The implantable prosthesis according to embodiment item 30. [Embodiment item 47] A base station, comprising a. A housing; b. It has a base station circuit disposed within the housing, and the base station circuit i. Receives at least one first signal representing movement from an implantable prosthesis, ii. Sends the at least one first signal to a destination, iii. Receives at least one second signal from a source, and iv. Is configured to send the at least one second signal to the implantable prosthesis. A base station. 〔Embodiment Item 48〕 The base station circuit according to Embodiment Item 47, wherein the base station circuit is configured to poll the implantable prosthesis for the first signal. 〔Embodiment Item 49〕 The base station circuit according to Embodiment Item 47, wherein the base station circuit is configured to decode the at least one first signal before sending the at least one first signal to the destination. 〔Embodiment Item 50〕 The base station circuit according to Embodiment Item 47, wherein the base station circuit is configured to encrypt the at least one first signal before sending the at least one first signal to the destination. 〔Embodiment Item 51〕 The base station circuit according to Embodiment Item 47, wherein the base station circuit is configured to decrypt the at least one first signal before sending the at least one first signal to the destination. 〔Embodiment Item 52〕 The base station circuit according to Embodiment Item 47, wherein the base station circuit is configured to encode the at least one first signal before sending the at least one first signal to the destination. 〔Embodiment Item 53〕 A method including the step of opening a fuse provided in an implantable prosthesis between a power source and an implantable circuit in response to a current passing through the fuse exceeding an overcurrent threshold value. 〔Embodiment Item 54〕 A method comprising the step of opening a fuse provided in an implantable prosthesis between a power source and an implantable circuit in response to a current passing through the fuse exceeding an overcurrent threshold for at least a threshold time. 〔Embodiment item 55〕 A method comprising the step of opening a fuse provided in an implantable prosthesis between a power source and an implantable circuit in response to a voltage applied across the fuse exceeding an overvoltage threshold. 〔Embodiment item 56〕 A method comprising the step of opening a fuse provided in an implantable prosthesis between a power source and an implantable circuit in response to a voltage applied across the fuse exceeding an overvoltage threshold for at least a threshold time. 〔Embodiment item 57〕 A method comprising the step of opening a fuse provided in an implantable prosthesis between a power source and an implantable circuit in response to a temperature exceeding an excess temperature threshold. 〔Embodiment item 58〕 A method comprising the step of opening a fuse provided in an implantable prosthesis between a power source and an implantable circuit in response to a temperature exceeding an excess temperature threshold for at least a threshold length of time. 〔Embodiment item 59〕 A method comprising: a. generating a sensor signal in response to movement of a patient in whom a prosthesis is implanted; and b. transmitting the sensor signal to a remote location. 〔Embodiment item 60〕 A method comprising: a. generating a sensor signal in response to movement of a patient in whom a prosthesis is implanted; b. sampling the sensor signal; and c. transmitting the sample to a remote location. 〔Embodiment item 61〕 A method comprising: a. Generating a sensor signal in response to the movement of a patient with an implanted prosthesis; b. Determining whether the sensor signal represents an eligible event; c. Transmitting the sensor signal to a remote location in response to the determination of whether the sensor signal represents an eligible event. A method comprising the steps of. 〔Embodiment item 62〕 A method, a. Generating a sensor signal in response to the movement of a patient with an implanted prosthesis; b. Receiving a polling signal from a remote location; c. Transmitting the sensor signal to the remote location in response to the polling signal. A method comprising the steps of. 〔Embodiment item 63〕 A method, a. Generating a sensor signal in response to the movement of a patient with an implanted prosthesis; b. Creating a message including the sensor signal or data representing the sensor signal; c. Transmitting the message to a remote location. A method comprising the steps of. 〔Embodiment item 64〕 A method, a. Generating a sensor signal in response to the movement of a patient with an implanted prosthesis; b. Generating a data packet including the sensor signal or data representing the sensor signal; c. Transmitting the data packet to a remote location. A method comprising the steps of. 〔Embodiment item 65〕 A method, a. Generating a sensor signal in response to the movement of a patient with an implanted prosthesis; b. Encrypting at least a portion of the sensor signal or data representing the sensor signal; c. Transmitting the encrypted sensor signal to a remote location. A method comprising the steps of. 〔Embodiment item 66〕 A method comprising: a. generating a sensor signal in response to movement of a patient with an implanted prosthesis; b. encoding at least a portion of the sensor signal or data representing the sensor signal; c. transmitting the encoded sensor signal to a remote location. 〔Embodiment Item 67〕 A method comprising: a. generating a sensor signal in response to movement of a patient with an implanted prosthesis; b. transmitting the sensor signal to a remote location; c. setting an implantable circuit associated with the prosthesis to a low power mode after transmission of the sensor signal. 〔Embodiment Item 68〕 A method comprising: a. generating a first sensor signal in response to movement of a patient with an implanted prosthesis; b. transmitting the first sensor signal to a remote location; c. setting at least one component of an implantable circuit associated with the prosthesis to a low power mode after transmission of the sensor signal; d. generating a second sensor signal in response to movement of the patient after elapse of a low power mode time for which the implantable circuit is to be set. 〔Embodiment Item 69〕 A method comprising: a. receiving a sensor signal from a prosthesis attached to or implanted in a patient; b. transmitting the received sensor signal to a destination. 〔Embodiment Item 70〕 A method comprising: a. sending an inquiry to a prosthesis attached to or implanted in a patient; b. receiving a sensor signal from the prosthesis after sending the inquiry. c. Transmitting the received sensor signal to a destination, a method comprising the steps of. 〔Embodiment Item 71〕 A method, a. Receiving a sensor signal and at least one identifier from a prosthesis attached to or implanted in a patient; b. Determining whether the identifier is correct; c. Transmitting the received sensor signal to a destination in response to the determination of whether the identifier is correct, a method comprising the steps of. 〔Embodiment Item 72〕 A method, a. Receiving a message containing a sensor signal from a prosthesis attached to or implanted in a patient; b. Decoding at least a portion of the message; c. Transmitting the decoded message to a destination, a method comprising the steps of. 〔Embodiment Item 73〕 A method, a. Receiving a message containing a sensor signal from a prosthesis attached to or implanted in a patient; b. Decrypting at least a portion of the message; c. Transmitting the decrypted message to a destination, a method comprising the steps of. 〔Embodiment Item 74〕 A method, a. Receiving a message containing a sensor signal from a prosthesis attached to or implanted in a patient; b. Encoding at least a portion of the message; c. Transmitting the encoded message to a destination, a method comprising the steps of. 〔Embodiment Item 75〕 A method, a. Receiving a message containing a sensor signal from a prosthesis attached to or implanted in a patient; c. encrypting at least a portion of the message; d. transmitting the encrypted message to a destination, a method. 〔Embodiment Item 76〕 A method comprising: a. receiving a data packet including a sensor signal from a prosthesis attached to or implanted in a patient; b. decrypting at least a portion of the data packet; c. transmitting the decrypted data packet to a destination, a method. 〔Embodiment Item 77〕 A method comprising: a. receiving a data packet including a sensor signal from a prosthesis attached to or implanted in a patient; b. decoding at least a portion of the data packet; c. transmitting the decoded data packet to a destination, a method. 〔Embodiment Item 78〕 A method comprising: a. receiving a data packet including a sensor signal from a prosthesis attached to or implanted in a patient; b. encoding at least a portion of the data packet; c. transmitting the encoded data packet to a destination, a method. 〔Embodiment Item 79〕 A method comprising: a. receiving a data packet including a sensor signal from a prosthesis attached to or implanted in a patient; b. encrypting at least a portion of the data packet; c. transmitting the encrypted data packet to a destination, a method. 〔Embodiment Item 80〕 A method comprising: a. Receiving a sensor signal from a prosthesis attached to or implanted within a patient; b. Decoding at least a portion of the sensor signal; c. Transmitting the decoded sensor signal to a destination, a method. 〔Embodiment Item 81〕 A method comprising: a. Receiving a sensor signal from a prosthesis attached to or implanted within a patient; b. Deciphering at least a portion of the sensor signal; c. Transmitting the deciphered sensor signal to a destination, a method. 〔Embodiment Item 82〕 A method comprising: a. Receiving a sensor signal from a prosthesis attached to or implanted within a patient; b. Encoding at least a portion of the sensor signal; c. Transmitting the encoded sensor signal to a destination, a method. 〔Embodiment Item 83〕 A method comprising: a. Receiving a sensor signal from a prosthesis attached to or implanted within a patient; b. Encrypting at least a portion of the sensor signal; c. Transmitting the encrypted sensor signal to a destination, a method. 〔Embodiment Item 84〕 An implantable circuit for an implantable prosthesis. 〔Embodiment Item 85〕 An implanted or implantable prosthesis having an implantable circuit. 〔Embodiment Item 86〕 An implanted or implantable prosthesis having a fuse. 〔Embodiment Item 87〕 A base station communicable with an implanted or implantable prosthesis.

[0265] D. Computer Systems for Analysis, Information Dissemination, Ordering, and Supply: Processing of IMU Data Recorded During Patient Monitoring As described in previous sections of this specification, the patient is intermittently monitored at home, within the work environment, at the physician's clinic, or in another environment where the patient frequently resides, in combination with sensors incorporated within the implant and a base station or other communication device. Sensor data is updated from the implant to the base station, temporarily stored within the base station during the accumulation of data in a patient monitoring session, and then transmitted from the base station to one or more stand-alone servers, data centers, or data processing applications running within a cloud computing facility. Also, as described in previous sections of this specification, the data is transmitted by means of a variety of mutually different forms of communication media, associated communication devices and subsystems, and communication services and functions of the operating system, using a variety of mutually different forms of data transmission protocols. The data is encoded and encrypted according to a predetermined format and digital coding convention. In the current section of this specification, it is assumed that the monitoring data is transmitted from the base station to the data processing application in a series of ordered messages. Assume that the data processing application interprets the time sequence of the encoded IMU data - vectors, patient identifier, device identifier, IMU setting parameters, and encoded IMU data - vectors described in more detail below, identifies the patient and the sensor-equipped implant, authorizes the receipt and processing of monitoring data from the patient, creates output results and output reports, and includes other information required by the data processing application for distributing the output results and output reports to various predetermined beneficiaries, such as physicians, insurance companies, and other such beneficiaries. In another embodiment, the monitoring data may be transmitted as one or more files by means of various file transfer protocols and facilities, although of course the file transfer protocol is run in preference to the message protocol. In a particular embodiment, the patient monitoring - session - data may be received on various forms of optical or electromagnetic data storage devices physically transported to a computer or computing facility that runs the data processing application.

[0266] The main task of the data import and monitoring data processing component of the data processing application is to convert the raw sensor data outputted by the sensors incorporated in the implant during the monitoring session into a human-readable report encoded in a digital format and / or a digital format encoded output result that is suitable for being sent to doctors, insurance companies, and / or additional automated systems for the next automated processing task. Additionally, the monitoring data processing component of the data processing application can issue various different types of events and warnings based on the output result of the monitoring session, and such events and warnings can be handled by other components of the data processing application or other applications that are simultaneously running within one or more computers or a distributed computer system.

[0267] In different embodiments, there are a very large number of different approaches that can be attempted to analyze the raw sensor data to produce the output result. Next, one approach will be described below with reference to FIGS. 28 to 37H. In variant embodiments, different and / or additional forms of sensor data may be included in and incorporated into the analysis of the monitoring data received by the data processing application from a number of different sensors. For example, the implant may include a temperature sensor, various forms of chemical sensors, acoustic sensors, and other forms of sensors, and the data output from such sensors may be useful in diagnosing many forms of problems and abnormalities that occur in different forms ...

Claims

1. A tibial insert for an implanted artificial knee joint, comprising a tibial insert in which the thickness on the inner side of the implant is 1 mm, 2 mm, 3 mm, 4 mm, 5 mm, 6 mm, 7 mm, 8 mm, 9 mm, or 10 mm greater than the thickness on the outer side of the implant.

2. A tibial insert for an implanted artificial knee joint, comprising a tibial insert in which the thickness on the outer side of the implant is 1 mm, 2 mm, 3 mm, 4 mm, 5 mm, 6 mm, 7 mm, 8 mm, 9 mm, or 10 mm greater than the thickness on the inner side of the implant.

3. A tibial insert for an implanted artificial knee joint, comprising a tibial insert in which the thickness on the front side of the implant is 1 mm, 2 mm, 3 mm, 4 mm, 5 mm, 6 mm, 7 mm, 8 mm, 9 mm, or 10 mm greater than the thickness on the rear side of the implant.

4. A tibial insert for an implanted artificial knee joint, comprising a tibial insert in which the thickness on the rear side of the implant is 1 mm, 2 mm, 3 mm, 4 mm, 5 mm, 6 mm, 7 mm, 8 mm, 9 mm, or 10 mm greater than the thickness on the front side of the implant.

5. A tibial insert or joint spacer for an implanted artificial knee joint, comprising a tibial insert in which the thickness of one of the inner side, outer side, front side, and / or rear side of the implant is 1 mm, 2 mm, 3 mm, 4 mm, 5 mm, 6 mm, 7 mm, 8 mm, 9 mm, or 10 mm greater than the thickness of the corresponding side of the implant, wherein the inner side and the outer side are corresponding sides, and the front side and the rear side are corresponding sides.

6. The tibial insert according to any one of claims 1 to 5, wherein the tibial insert is made of polyethylene or polyetheretherketone (PEEK).

7. The tibial insert according to any one of claims 1 to 6, wherein the tibial insert is customized according to the patient.

8. The tibial insert according to any one of claims 1 to 7, wherein the tibial insert is manufactured by 3D printing or molding.

9. An implanted medical device, A circuit configured to be fixedly attached to an implantable artificial device, a power component, and a device configured to disconnect the circuit from the power component, an implantable medical device. **Claim 10** An implantable medical device, comprising a circuit configured to be fixedly attached to an implantable artificial device, a battery, and a fuse coupled between the circuit and the battery, an implantable medical device. **Claim 11** A method comprising the step of electrically opening a fuse disposed between a circuit and a battery, wherein at least the fuse and the circuit are provided in an implantable artificial device. **Claim 12** An implantable medical device, comprising at least one sensor configured to generate a sensor signal, and a control circuit configured to generate the sensor signal at a frequency associated with a telemedicine code for the at least one sensor, an implantable medical device. **Claim 13** An implantable medical device, comprising at least one sensor configured to generate a sensor signal, and a control circuit configured to generate the sensor signal at a frequency that enables a physician to be eligible for payment under a telemedicine insurance code for the at least one sensor, an implantable medical device. **Claim 14** An implantable medical device, comprising at least one sensor configured to generate a sensor signal, and a control circuit configured to generate the sensor signal at a frequency that enables a physician to be eligible for full payment under a telemedicine insurance code for the at least one sensor, an implantable medical device. **Claim 15** A method comprising the step of generating a sensor signal associated with an implantable medical device at a frequency that enables a physician to be eligible for payment under a telemedicine insurance code. **Claim 16** A method comprising the step of generating a sensor signal associated with an implantable medical device at a frequency that enables a physician to be eligible for full payment under a telemedicine insurance code. **Claim 17** An implantable prosthesis, comprising a housing, and an implantable circuit disposed within the housing, wherein the implantable circuit is generate at least one first signal representing movement, determine whether the at least one first signal meets at least one first criterion, and an implantable prosthesis configured to send the at least one first signal to a remote location in response to a determination that the at least one first signal meets the at least one first criterion. **Claim 18** A base station, comprising a housing, and a base station circuit disposed within the housing, wherein the base station circuit is configured to receive at least one first signal representing movement from an implantable prosthesis, send the at least one first signal to a destination, receive at least one second signal from a source, and send the at least one second signal to the implantable prosthesis. **Claim 19** A method comprising opening a fuse provided in an implantable prosthesis between a power source and an implantable circuit in response to a current through the fuse exceeding an overcurrent threshold. **Claim 20** A method comprising opening a fuse provided in an implantable prosthesis between a power source and an implantable circuit in response to a current through the fuse exceeding an overcurrent threshold for at least a threshold time period. **Claim 21** A method comprising opening a fuse provided in an implantable prosthesis between a power source and an implantable circuit in response to a voltage across the fuse exceeding an overvoltage threshold. **Claim 22** A method comprising opening a fuse provided in an implantable prosthesis between a power source and an implantable circuit in response to a voltage across the fuse exceeding an overvoltage threshold for at least a threshold time period. **Claim 23** A method comprising opening a fuse provided in an implantable prosthesis between a power source and an implantable circuit in response to a temperature exceeding an over-temperature threshold. **Claim 24** A method comprising opening a fuse provided in an implantable prosthesis between a power source and an implantable circuit in response to a temperature exceeding an over-temperature threshold for at least a threshold length of time. **Claim 25** A method comprising generating a sensor signal in response to movement of a patient in which the prosthesis is implanted, A method comprising the step of transmitting the sensor signal to a remote location. **Claim 26** A method comprising: generating a sensor signal in response to the movement of a patient with a prosthesis implanted; sampling the sensor signal; transmitting the sample to a remote location. **Claim 27** A method comprising: generating a sensor signal in response to the movement of a patient with a prosthesis implanted; determining whether the sensor signal represents an eligible event; transmitting the sensor signal to a remote location in response to the determination of whether the sensor signal represents an eligible event. **Claim 28** A method comprising: generating a sensor signal in response to the movement of a patient with a prosthesis implanted; receiving a polling signal from a remote location; transmitting the sensor signal to the remote location in response to the polling signal. **Claim 29** A method comprising: generating a sensor signal in response to the movement of a patient with a prosthesis implanted; creating a message including the sensor signal or data representing the sensor signal; transmitting the message to a remote location. **Claim 30** A method comprising: generating a sensor signal in response to the movement of a patient with a prosthesis implanted; generating a data packet including the sensor signal or data representing the sensor signal; transmitting the data packet to a remote location. **Claim 31** A method comprising: generating a sensor signal in response to the movement of a patient with a prosthesis implanted; encrypting at least a portion of the sensor signal or data representing the sensor signal; transmitting the encrypted sensor signal to a remote location. **Claim 32** A method comprising: generating a sensor signal in response to the movement of a patient with a prosthesis implanted; encoding at least a portion of the sensor signal or data representing the sensor signal; transmitting the encoded sensor signal to a remote location. **Claim 33** A method comprising: generating a sensor signal in response to the movement of a patient with a prosthesis implanted; transmitting the sensor signal to a remote location. A method comprising the step of setting an implantable circuit associated with the prosthesis to a low power mode after transmission of the sensor signal.

34. A method comprising: generating a first sensor signal in response to movement of a patient with an implanted prosthesis; transmitting the first sensor signal to a remote location; setting at least one component of an implantable circuit associated with the prosthesis to a low power mode after transmission of the sensor signal; generating a second sensor signal in response to movement of the patient after elapse of a low power mode time for which the implantable circuit is to be set.

35. A method comprising: receiving a sensor signal from a prosthesis attached to or implanted in a patient; transmitting the received sensor signal to a destination.

36. A method comprising: sending an inquiry to a prosthesis attached to or implanted in a patient; after sending the inquiry, receiving a sensor signal from the prosthesis; transmitting the received sensor signal to a destination.

37. A method comprising: receiving a sensor signal and at least one identifier from a prosthesis attached to or implanted in a patient; determining whether the identifier is correct; transmitting the received sensor signal to a destination in response to the determination of whether the identifier is correct.

38. A method comprising: receiving a message including a sensor signal from a prosthesis attached to or implanted in a patient; decoding at least a portion of the message; transmitting the decoded message to a destination.

39. A method comprising: receiving a message including a sensor signal from a prosthesis attached to or implanted in a patient; decrypting at least a portion of the message; transmitting the decrypted message to a destination.

40. A method comprising: receiving a message including a sensor signal from a prosthesis attached to or implanted in a patient; encoding at least a portion of the message; A method comprising the step of transmitting the encoded message to a destination. **Claim 41** A method comprising: Receiving a message including a sensor signal from a prosthesis attached to or implanted within a patient; Encoding at least a portion of the message; Transmitting the encoded message to a destination. **Claim 42** A method comprising: Receiving a data packet including a sensor signal from a prosthesis attached to or implanted within a patient; Decoding at least a portion of the data packet; Transmitting the decoded data packet to a destination. **Claim 43** A method comprising: Receiving a data packet including a sensor signal from a prosthesis attached to or implanted within a patient; Decrypting at least a portion of the data packet; Transmitting the decrypted data packet to a destination. **Claim 44** A method comprising: Receiving a data packet including a sensor signal from a prosthesis attached to or implanted within a patient; Encoding at least a portion of the data packet; Transmitting the encoded data packet to a destination. **Claim 45** A method comprising: Receiving a data packet including a sensor signal from a prosthesis attached to or implanted within a patient; Encrypting at least a portion of the data packet; Transmitting the encrypted data packet to a destination. **Claim 46** A method comprising: Receiving a sensor signal from a prosthesis attached to or implanted within a patient; Decoding at least a portion of the sensor signal; Transmitting the decoded sensor signal to a destination. **Claim 47** A method comprising: Receiving a sensor signal from a prosthesis attached to or implanted within a patient; Decrypting at least a portion of the sensor signal; Transmitting the decrypted sensor signal to a destination. **Claim 48** A method comprising: Receiving a sensor signal from a prosthesis attached to or implanted within a patient; Encoding at least a portion of the sensor signal; Transmitting the encoded sensor signal to a destination, a method comprising. **Claim 49** A method comprising: Receiving a sensor signal from a prosthesis attached to or implanted within a patient; Encrypting at least a portion of the sensor signal; Transmitting the encrypted sensor signal to a destination, a method comprising. **Claim 50** An implantable circuit for an implantable prosthesis. **Claim 51** An implantable prosthesis having an implantable circuit. **Claim 52** An implantable prosthesis having a fuse. **Claim 53** A base station capable of communicating with an implantable prosthesis. **Claim 54** A monitoring-session-data collection, analysis, and status reporting system embodied as a component of one or more computer systems, each computer system including one or more processors, one or more memories, one or more network connection means, and access to one or more mass storage devices, said one or more monitoring-session-data collection, data analysis, and status reporting systems comprising: A monitoring-session-data receiving component that receives monitoring-session-data including acceleration data generated by a sensor provided within or near a prosthesis attached to or implanted within a patient from an external monitoring-session-data source and stores the received monitoring-session-data in the one or more memories and the one or more mass storage devices; Including a monitoring-session-data processing component, said monitoring-session-data processing component comprising: Preparing the monitoring-session-data for processing; Determining a component trajectory representing a motion mode and additional metric values from the monitoring-session-data; Including a monitoring-session-data analysis component, said monitoring-session-data analysis component comprising: Deriving the state of the prosthesis and the state of the patient from the motion mode and the additional metric values. Deliver the determined prosthesis state and patient state to a target computer system via the network connection means, and A monitoring-session-data collection, analysis, and status reporting system that delivers one or more warnings and events to a target computer system via the network connection means when instructed by the determined prosthesis state and patient state.

55. The monitoring-session-data collection, analysis, and status reporting system according to claim 54, wherein the monitoring-session-data includes a patient identifier, an instrument identifier, a time stamp, device configuration data, and an ordered set of data.

56. The ordered set of data is A time series of data-vectors each containing values associated with linear acceleration with respect to three coordinate axes of an internal device coordinate system, and The monitoring-session-data collection, analysis, and status reporting system according to claim 55, including one of a time series of data-vectors each containing values associated with linear acceleration with respect to three coordinate axes of a first internal device coordinate system and values associated with angular velocity, and values associated with angular velocity with respect to the first internal device coordinate system or a second internal device coordinate system.

57. The monitoring-session-data processing component Receives a time series of data-vectors each containing three values associated with linear acceleration in the directions of three coordinate axes of a first internal device coordinate system and three values associated with angular velocity about each axis of the first or second internal device coordinate system, If rescaling of the data-vector series is required, scale the values of the data-vector, If normalization of the data-vector series is required, normalize the values of the data-vector, If it is necessary to associate one or more of the values associated with the linear acceleration and the values associated with the angular velocity with a common internal coordinate system, convert one or more of the values associated with the linear acceleration and the values associated with the angular velocity to be associated with the common internal coordinate system, and If the time series of the data-vectors needs to be synchronized with respect to a fixed interval time series, preparing the monitoring-session-data for processing by synchronizing the data-vectors with respect to the fixed interval time series, the monitoring-session-data collection, analysis, and status reporting system according to claim 54.

58. The monitoring-session-data processing component orient the prepared monitoring-session-data having a data-vector that includes three numerical values each associated with the linear acceleration in the directions of the three coordinate axes of the internal device coordinate system and includes three numerical values each associated with the angular velocity about each axis of the internal device coordinate system, with respect to the natural coordinate system, perform band-pass filtering on the oriented data-vectors to obtain a set of data-vectors for each of a number of frequencies including normal motion frequencies, determine the spatial amplitude in each of the coordinate axis directions of the natural coordinate system from the data-vectors for each of the abnormal motion frequencies, determine the spatial amplitude in each of the coordinate axis directions of the natural coordinate system from the basic trajectory for the patient and the data-vectors for the normal motion frequencies, and determine the current normal motion characteristics from the basic trajectory for the patient and the data-vectors for the normal motion frequencies, deduce a component trajectory representing the motion mode and additional metric values from the monitoring-session-data, the monitoring-session-data collection, analysis, and status reporting system according to claim 54.

59. The step of determining the spatial amplitude in each of the coordinate axis directions of the natural coordinate system from the data-vectors for the frequencies includes further steps of generating a spatial trajectory from the data-vectors, projecting the spatial frequencies onto each of the coordinate axes, and determining the projection lengths of the spatial frequencies onto each of the coordinate axes, the monitoring-session-data collection, analysis, and status reporting system according to claim 58.

60. The monitoring-session-data analysis component determines the prosthesis state and the patient state from the motion mode and the additional metric values Submit the motion mode and the additional metric values to a decision tree that generates a diagnosis-and-suggestion report, Determine by packaging the diagnosis-and-suggestion report together with the amplitude generated for the motion mode, the metrics generated from the normal motion frequency trajectory and the basic trajectory, and one or both of the output report and output data values characterizing the prosthesis state and the patient state, the monitoring-session-data collection, analysis, and status reporting system of claim 54. **Claim 61** The one or more warnings and events distributed to the target computer system by the monitoring-session-data analysis component are Warnings that notify a physician or a medical facility that the patient requires immediate assistance or intervention, Events that indicate additional care and / or equipment required by the patient, the additional care and / or equipment being handleable by various external computer systems to automatically provide the additional care and / or equipment to the patient or to notify the patient of the additional care and / or equipment and provide information regarding acquisition of the additional care and / or equipment by the patient, the monitoring-session-data collection, analysis, and status reporting system of claim 54. **Claim 62** A method implemented by a monitoring-session-data collection, analysis, and status reporting system embodied as components of one or more computer systems, each computer system including one or more processors, one or more memories, one or more network connection means, and access to one or more mass storage devices, the method comprising: Receiving monitoring-session-data including acceleration data generated by a sensor provided within or proximate to a prosthesis attached to or implanted within a patient from an external monitoring-session-data source; Storing the received monitoring-session-data in one or more of the one or more memories and the one or more mass storage devices; Determining the state of the prosthesis and the state of the patient from the motion mode and additional metric values; Delivering the determined prosthesis state and patient state to a target computer system via the network connection means; Delivering, when instructed by the determined prosthesis state and patient state, one or more warnings and events to the target computer system via the network connection means, a method.

63. The step of determining the prosthesis state and patient state from the motion mode and the additional metric values Preparing the monitoring - session - data for processing; Determining component trajectories representing the motion mode and additional metric values from the monitoring - session - data; Submitting the motion mode and the additional metric values to a decision tree that generates a diagnostic and advisory report; Packaging the diagnostic and advisory report together with the amplitude generated for the motion mode, the metrics generated from the normal motion frequency trajectory and the basic trajectory, and one or both of the output report and output data values characterizing the prosthesis state and the patient state, the additional metric values, the method according to claim 62.

64. The step of preparing the monitoring - session - data for processing Receiving a time series of data - vectors each containing three numerical values associated with the linear acceleration in the directions of the three coordinate axes of a first internal device coordinate system and three numerical values associated with the angular velocity about each axis of the first or second internal device coordinate system; Scaling the numerical values of the data - vectors when rescaling of the data - vector series is required; Normalizing the numerical values of the data - vectors when normalization of the data - vector series is required; Converting one or more of the numerical values associated with the linear acceleration and the numerical values associated with the angular velocity when conversion of one or more of the numerical values associated with the linear acceleration and the numerical values associated with the angular velocity is required to associate them with a common internal coordinate system, converting one or more of the numerical values associated with the linear acceleration and the numerical values associated with the angular velocity to associate them with the common internal coordinate system; If the time series of the data-vectors needs to be synchronized with respect to a fixed interval time series, the method according to claim 62 further comprising the step of synchronizing the data-vectors with respect to the fixed interval time series.

65. The step of obtaining from the monitoring-session-data a component trajectory representing a motion mode and additional metric values comprises orienting the prepared monitoring-session-data having a data-vector including three numerical values each associated with a linear acceleration in the directions of three coordinate axes of an internal device coordinate system and including three numerical values each associated with an angular velocity about each axis of the internal device coordinate system, with respect to a natural coordinate system; band-pass filtering the oriented data-vector to obtain a set of data-vectors for each of a number of frequencies including normal motion frequencies; determining a spatial amplitude in each of the coordinate axis directions of the natural coordinate system from the data-vectors for each of the abnormal motion frequencies; determining a spatial amplitude in each of the coordinate axis directions of the natural coordinate system from a basic trajectory for the patient and the data-vectors for the normal motion frequencies; the method according to claim 62 further comprising determining current normal motion characteristics from the basic trajectory for the patient and the data-vectors for the normal motion frequencies.

66. The step of determining a spatial amplitude in each of the coordinate axis directions of the natural coordinate system from the data-vectors for a frequency comprises generating a spatial trajectory from the data-vector; projecting the spatial frequency onto each of the coordinate axes; the method according to claim 62 further comprising determining a projection length of the spatial frequency onto each of the coordinate axes.

67. The step of deriving a prosthesis state and a patient state from the motion mode and the additional metric values comprises submitting the motion mode and the additional metric values to a decision tree that generates a diagnostic and advisory report. The method according to claim 62, further comprising the step of packaging the diagnostic and advisory report together with additional metric values that result in one or both of an amplitude resulting from the motion mode, a metric resulting from a normal motion frequency trajectory and a basic trajectory, and an output report and output data values characterizing the prosthesis state and the patient state.

68. The one or more warnings and events distributed to the target computer system by the monitoring-session-data analysis component include warnings that notify the patient's physician or healthcare facility that immediate assistance or intervention is required, include events that direct additional care and / or equipment required by the patient, and the additional care and / or equipment is handleable by various external computer systems to automatically provide the additional care and / or equipment to the patient or to notify the patient of the additional care and / or equipment and provide information regarding acquisition of the additional care and / or equipment by the patient. The method according to claim 62.

69. A physical data storage device encoded with computer instructions, wherein when the computer instructions are executed by one or more processors provided within one or more computer systems of a monitoring-session-data collection, analysis, and status reporting system, each computer system including access to one or more processors, one or more memories, one or more network connection means, and one or more mass storage devices A physical data storage device that controls the monitoring-session-data collection, analysis, and status reporting system to receive monitoring-session-data including acceleration data generated by a sensor provided within or proximate to a prosthesis attached to or implanted within a patient.

70. A method of determining joint laxity within the body of a patient having an implanted artificial joint, the method comprising: a) analyzing the movement of the implanted artificial joint; and b) comparing the movement to a prior / standardized reference.

71. A method of determining laxity of an implanted prosthesis within the body of a patient in whom the prosthesis has been implanted a) obtaining a standardized criterion of movement by analyzing the movement of an implanted prosthesis during one or more first monitoring sessions; b) obtaining a current content of movement by analyzing the movement of the implanted prosthesis during one or more second monitoring sessions following the one or more first monitoring sessions; c) comparing the current content of movement with the standardized criterion of movement, thereby detecting loosening of the implanted prosthesis in the body of a patient provided with the implanted prosthesis. A method comprising.

72. A method for determining a clinical or pre-clinical state associated with an implant in a patient's body, the method comprising: a. monitoring a first movement of the implant during a first monitoring session using a sensor directly coupled to the implant to provide first monitoring-session data regarding the first movement; b. monitoring a second movement of the implant during a second monitoring session using the sensor to provide second monitoring-session data regarding the second movement; c. comparing the first monitoring-session data or a processing result thereof with the second monitoring-session data or a processing result thereof to provide a comparison result representing a clinical or pre-clinical state associated with the implant. A method comprising.

73. The method according to claim 72, wherein the clinical or pre-clinical state is optionally loosening of the implant due to a lucency around the prosthesis or osteolysis around the prosthesis.

74. The method according to claim 72, wherein the clinical or pre-clinical state is misalignment or readjustment of the implant.

75. The method according to claim 72, wherein the clinical or pre-clinical state is deformation of the implant.

76. The patient is asymptomatic with respect to the clinical or pre-clinical state, and the comparison result of the first and second data or the processing result of the data indicates that the state has occurred between the first monitoring session and the second monitoring session. The method according to claim 72.

77. The method according to claim 72, wherein the patient is asymptomatic with respect to loosening of the implant, and the comparison result of the first and second data or the processing result of the data indicates that the implant appears to have loosened between the first monitoring session and the second monitoring session.

78. The method according to claim 72, wherein the patient is asymptomatic with respect to readjustment of the implant, and the comparison result of the first and second data or the processing result of the data indicates that the implant appears to have changed alignment between the first monitoring session and the second monitoring session.

79. The method according to claim 72, wherein the patient is asymptomatic with respect to deformation of the implant, and the comparison result of the first and second data or the processing result of the data indicates that the implant appears to have deformed between the first monitoring session and the second monitoring session.

80. A method of treating a clinical or preclinical condition associated with an implant in a patient's body, a. comprising the step of identifying an implant in the patient's body, the implant presenting a clinical or preclinical condition, b. comprising the step of attaching a corrective external brace to the patient to restore proper alignment and / or improved stability to the implant.

81. The method according to claim 80, wherein the corrective external brace is specially customized to the patient and the preclinical condition.

82. A method of treating a clinical or preclinical condition associated with an implant in a patient's body, a. comprising the step of identifying an implant in the patient's body, the implant presenting a clinical or preclinical condition, b. comprising the step of contacting the implant with a fixation system to retard the progression of the preclinical condition.

83. The method according to claim 82, wherein the fixation system comprises hardware selected from K-wires, pins, screws, plates, and intramedullary devices.

84. The screw holding the implant is disposed through the bone, and the end of the screw presses against the surface of the implant to prevent movement of the implant. The screw is selected from 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, and 20 screws. The method according to claim 82.

85. The fixation system includes bone cement. The method according to claim 82.

86. A method for treating a clinical or preclinical condition associated with an implant in a patient's body, a. comprising the step of identifying an implant in the patient's body, the implant presenting a clinical or preclinical condition, b. comprising the step of contacting a tamp, the contact changing the location of the implant in the patient's body.

87. The preclinical condition is readjustment of the implant. The method according to claim 86.

88. A method for treating a clinical or preclinical condition associated with an implant in a patient's body, a. comprising the step of identifying an implant in the patient's body, the implant presenting a clinical or preclinical condition, b. comprising the step of implanting an insert adjacent to a component of the implant, the insert adjusting the force acting on the component of the implant.

89. The insert is a tibial insert. The method according to claim 88.

90. The insert is a tibial insert having (i) an outer side with a minimum thickness and (ii) an inner side with a minimum thickness different from the minimum thickness of the outer side. The method according to claim 88.

91. A method for treating a clinical or preclinical condition associated with an implant in a patient's body, a. comprising the step of identifying an implant in the patient's body, the implant presenting a clinical or preclinical condition, b. comprising the step of delivering an osteo-integration agent to a location around the implant.

92. The osteo-integration agent is selected from autologous bone graft, allogeneic bone graft, synthetic bone graft, bone paste, bone growth factor, and growth factor. The method according to claim 91.

93. A method for treating a clinical or pre-clinical condition associated with an implant in a patient, comprising: a. identifying an implant in the patient's body, the implant presenting a clinical or pre-clinical condition; b. delivering an antibacterial agent to a location around the implant. **Claim 94** The method according to claim 93, wherein the antibacterial agent is formulated in a sustained release form. **Claim 95** The method according to any one of claims 72 to 94, wherein the implant is an intelligent implant. **Claim 96** The method according to any one of claims 72 to 94, wherein the implant is selected from a knee joint implant, a hip joint implant, and a shoulder joint implant. **Claim 97** The method according to any one of claims 72 to 94, wherein the processing result of the monitoring - session - data consists of a motion mode. **Claim 98** The method according to any one of claims 72 to 94, wherein the processing result of the monitoring - session - data consists of a motion mode, and the state of the implant is deduced from the motion mode. **Claim 99** The method according to any one of claims 72 to 94, wherein the processing result of the monitoring - session - data consists of a motion mode, and the state of the patient is deduced from the motion mode. **Claim 100** The method according to any one of claims 72 to 94, wherein the implant is placed in the patient's body at least 10 weeks prior to the first monitoring session. **Claim 101** The method according to any one of claims 72 to 94, wherein the implant changes alignment over a period of at least 2 weeks. **Claim 102** The method according to any one of claims 72 to 94, wherein the implant loosens over a period of at least 2 weeks. **Claim 103** The method according to any one of claims 72 to 94, wherein the implant deforms over a period of at least 2 weeks. **Claim 104** The method according to any one of claims 72 to 94, wherein the implant has a control circuit configured to cause the sensor to generate a sensor signal at a frequency associated with a telemedicine code for the clinical or pre - clinical condition. **Claim 105** The implant has a control circuit configured to cause the sensor to generate a sensor signal at a frequency that enables a physician to be eligible for payment under a telemedicine insurance code, and the sensor signal is generated at the frequency, and is the method according to any one of claims 72 to 94.

106. The implant has a control circuit configured to cause the sensor to generate a sensor signal at a frequency that enables a physician to be eligible for full payment under a telemedicine insurance code, and the sensor signal is generated at the frequency, and is the method according to any one of claims 72 to 94.

107. The method according to any one of claims 72 to 94, further comprising the step of generating a sensor signal associated with the implant at a frequency at which (i) a physician is eligible for full payment available under a telemedicine insurance code, or (ii) a physician can be eligible for payment available under a telemedicine insurance code.

108. A method comprising: a. providing an intelligent prosthesis implanted into bone adjacent to a joint of a patient, wherein an accelerometer is housed within the intelligent prosthesis and the accelerometer is positioned within the bone; b. moving the implanted intelligent prosthesis relative to an external environment, wherein the patient is positioned at a location where the implanted intelligent prosthesis is moved during a first monitoring session; c. during the first monitoring session, performing a first measurement with the accelerometer, the first measurement providing first monitoring-session-data or a processed result thereof that identifies a state of the implanted intelligent prosthesis at a time of the first measurement.

109. The method according to claim 108, wherein the accelerometer is a plurality of accelerometers.

110. The method according to claim 108, wherein the accelerometer is selected from a uniaxial accelerometer, a biaxial accelerometer, and a triaxial accelerometer.

111. The method according to claim 108, wherein the accelerometer operates in a broadband mode.

112. The method according to claim 108, wherein the bone is a tibia.

113. The method according to claim 108, wherein the accelerometer is disposed within a tibial extension of the intelligent prosthesis.

114. The method according to claim 108, wherein the implanted intelligent prosthesis is moved relative to the external environment without an impact force being applied to the patient or the intelligent prosthesis during the first monitoring session.

115. The method according to claim 108, wherein the external environment consists of the patient's residence.

116. The method according to claim 108, wherein the external environment consists of an operating room, and the intelligent prosthesis is implanted in the patient's body.

117. The method according to claim 108, wherein the state of the implanted intelligent prosthesis is an evaluation of the relaxation characteristics of the implanted intelligent prosthesis within the bone.

118. The method according to claim 108, wherein the state of the implanted intelligent prosthesis is an evaluation of the alignment characteristics of the implanted intelligent prosthesis within the bone.

119. The method according to claim 108, wherein the state of the implanted intelligent prosthesis is an evaluation of the wear characteristics of the implanted intelligent prosthesis.

120. The method according to claim 108, wherein the state of the implanted intelligent prosthesis is an evaluation of the bacterial infection characteristics of the bone region located adjacent to the implanted intelligent prosthesis.

121. The method according to claim 108, wherein the state of the implanted intelligent prosthesis indicates a pre-clinical state.

122. Step b) is repeated after a waiting period, and the repetition of step b) includes moving the implanted intelligent prosthesis relative to the external environment in which the patient is located. The implanted intelligent prosthesis is moved during a second monitoring session, and a second measurement is performed with the accelerometer during the second monitoring session. The second measurement provides second monitoring-session-data or second monitoring-session-data processing results for identifying the state of the implanted intelligent prosthesis at the second measurement time point.

123. Step b) is repeated a plurality of times, the plurality of times being separated from each other by waiting periods that are the same or different, the repetition of step b) including the step of moving the implanted intelligent prosthesis relative to the external environment in which the patient is located, the implanted intelligent prosthesis being moved during a plurality of monitoring sessions, measurements being taken with the accelerometer between each of the plurality of monitoring sessions, the measurements providing a plurality of monitoring-session-data or a processing result of a plurality of monitoring-session-data, each identifying the state of the implanted intelligent prosthesis at the time of the measurement, according to the method of claim 108.

124. Step b) is repeated a plurality of times, the plurality of times being separated from each other by waiting periods that are the same or different, the repetition of step b) including the step of moving the implanted intelligent prosthesis relative to the external environment in which the patient is located, the implanted intelligent prosthesis being moved during a plurality of monitoring sessions, measurements being taken with the accelerometer between each of the plurality of monitoring sessions, the measurements providing a plurality of monitoring-session-data or a processing result of a plurality of monitoring-session-data, each identifying the state of the implanted intelligent prosthesis at the time of the measurement, the plurality of monitoring-session-data being selected, optionally, from 2 to 20 monitoring sessions, the plurality of monitoring-session-data, when considered together, indicating a change in the state of the implanted intelligent prosthesis during the time when the plurality of monitoring sessions took place, according to the method of claim 108.

125. The change in the state represents the healing state of the tissue around the implanted intelligent prosthesis, according to the method of claim 124.

126. The change in the state represents the infection state of the tissue around the implanted intelligent prosthesis, according to the method of claim 124.

127. The change in the state represents the loosening of the implanted intelligent prosthesis within the bone, according to the method of claim 124.

128. The method according to claim 124, wherein the change in the state represents wear of the implanted intelligent prosthesis. **Claim 129** The method according to claim 124, wherein the change in the state represents misalignment of the implanted intelligent prosthesis. **Claim 130** The method according to claim 124, wherein the change in the state represents a change in the alignment of the implanted intelligent prosthesis.

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