Systems and methods for providing guidance for robotic medical procedures

Abstract

To provide a computer-implemented method for generating and presenting an electronic display of guidance for performing a robotic medical procedure.SOLUTION: A computer-implemented method for generating and presenting an electronic display of guidance for performing a robotic medical procedure, includes: receiving a plurality of prior procedure data sets; receiving or identifying objective data defining one or more of a duration and a patient outcome of the robotic medical procedure; executing an algorithm to identify a pattern across the plurality of prior procedure data sets; receiving information about an instance of the robotic medical procedure to be performed in the future for a patient outside the population; automatically generating guidance for performing the robotic medical procedure; and generating and presenting an electronic display of the guidance.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention mainly relates to providing guidance for robotic surgical procedures. More particularly, the present invention relates to collecting and analyzing data from previous procedures to generate guidance for robotic surgical procedures.

Background Art

[0002] Medical practitioners may use robotic devices to assist in performing medical procedures. The robotic device operates in cooperation with a computer system and other devices (e.g., components of a navigation system) to construct a robotic system. The robotic system receives and stores various information related to a specific procedure to be performed by the practitioner, such as information about the patient and information about the surgical plan. For example, for a knee surgery, the surgical plan may include the type of procedure to be performed (e.g., total knee arthroplasty or unicompartmental knee arthroplasty), the tissue and bone modifications necessary to prepare the bone to receive the implant, and the type of implant to be implanted within the patient. The robotic system can also perform various functions during the execution of the surgical plan, such as tracking the patient and assisting the practitioner in modifying the patient's anatomical structure (e.g., tissue, bone) according to the plan.

[0003] The robotic system can also acquire information during the course of a medical procedure. This information may be related to any number of characteristics of the medical procedure. The information may describe specific characteristics of the execution of the procedure, such as how long a particular part of the procedure took, which instruments were used during the course of the procedure, or how the practitioner performed a particular bone shaping. The information may describe characteristics of the procedure related to the patient, the environment, or other inputs related to the procedure. For example, the characteristics may be the patient's height, weight, the type of procedure performed, or the surgical room setup.

Summary of the Invention

[0004] Aspects of the present invention relate to, among other things, collecting and analyzing information obtained during the robotic medical procedure in order to provide guidance for the robotic medical procedure. Each of the aspects disclosed herein may include one or more of the specific matters described in connection with any of the other disclosed aspects.

[0005] In one example, a method executed by a computer to generate and display an electronic screen of guidance for performing the robotic medical treatment includes, by one or more processing devices, i) corresponding to the robotic medical treatment performed by using a robotic instrument on a patient within a population, and ii) receiving a plurality of prior treatment data sets, each of which defines one or more of a patient involved in the robotic medical treatment, a medical device, or an arrangement or operation of the robotic instrument, a pressing force by the robotic instrument, or a timing of a step of the robotic medical treatment; receiving or identifying object data that defines one or more of a period of the robotic medical treatment or an outcome of the patient by the one or more processing devices; executing an algorithm stored in a non-transitory computer-readable storage medium to identify a pattern that describes one or more of a patient involved in the robotic medical treatment, an arrangement or operation of the medical device or the robotic instrument, a pressing force by the robotic instrument, or a timing of a step of the robotic medical treatment to achieve the period defined by the object data over the plurality of prior treatment data sets; receiving, by the one or more processing devices, information about the robotic medical treatment to be performed in the future for a patient outside the population; automatically generating, by the one or more processing devices, the guidance for performing the robotic medical treatment, the guidance comprising a recommended arrangement or operation of a patient, a medical device, or a robotic instrument involved in the robotic medical treatment, a pressing force by the robotic instrument, or a timing of a step of the robotic medical treatment, based on an evaluation of the pattern identified over the plurality of prior treatment data sets and information for performing the robotic medical treatment received for the robotic medical treatment to be performed; and generating and displaying an electronic screen of the guidance.

[0006] The method may additionally or alternatively include one or more of the following specific matters or steps. That is, the period determined by the object data may be a part of the period of the robotic medical treatment, and the step of identifying the pattern across the plurality of previous treatment data sets may include identifying at least one occurrence level of the arrangement or movement of the patient, medical device, or robotic instrument across the plurality of previous treatment data sets. The step of identifying the pattern across the plurality of previous treatment data sets may include describing the operation of the robotic instrument in a part of the process of the robotic medical treatment achieved during the period determined by the object data. The information about the robotic medical treatment to be implemented may include information about at least one of the patient, the type of treatment, the characteristics of the operating room, or the user's past experience. The guidance may include the recommended timing of the steps of the robotic medical treatment, and the recommendation may include the recommended order of the steps of the robotic medical treatment.

[0007] In another example, a system for generating and displaying an electronic screen of guidance for performing a robotic medical procedure may include a computer-readable storage medium storing instructions for generating and displaying an electronic screen of guidance for performing the robotic medical procedure, and one or more processing devices, the one or more processing devices being configured to execute instructions to implement a method including a plurality of steps, the plurality of steps corresponding to i) the robotic medical procedure performed by using a robotic instrument on a patient within a population and ii) receiving a plurality of prior treatment data sets each containing robotic data obtained from a robotic device associated with the robotic instrument, receiving or identifying objective data defining one or more of the duration of the robotic medical procedure or the patient's outcome, identifying a pattern describing the characteristics of the robotic medical procedure or the patient's outcome achieved during the period defined by the objective data across the plurality of prior treatment data sets, receiving information about the robotic medical procedure to be performed in the future on patients outside the population, automatically generating guidance for performing the robotic medical procedure based on the characteristics identified by the pattern and the information received about the robotic medical procedure to be performed, and generating and displaying an electronic screen of guidance for performing the robotic medical procedure.

[0008] This system may additionally or alternatively include one or more of the following specific items or steps. That is, the characteristics of the robot data may be one or more of a patient involved in the robot medical treatment, the arrangement or operation of a medical device or a robot instrument, the pressing force by the robot instrument, or the timing of the steps of the robot medical treatment. The guidance may include the recommended arrangement or operation of a patient, a medical device or a robot instrument involved in the robot medical treatment, the pressing force by the robot instrument, or the timing of the steps of the robot medical treatment. The robot data may include information collected by the robot device during the process of the robot medical treatment. The step of identifying the pattern may include determining the occurrence level of the characteristics over a plurality of input treatments. The characteristics may be the order of treatment steps. The step of identifying the pattern may include determining the order of the treatment steps to be achieved during the period defined by the object data. The information about the robot medical treatment to be implemented may include information about at least one of a patient, the type of treatment, the characteristics of the operating room, or the past experience of the user.

[0009] In yet another aspect, the non-transitory computer-readable storage medium may have instructions that, when executed by a processing device, cause the processing device to implement a method for generating and displaying an electronic screen of guidance for performing a robotic medical procedure, the method being: (i) corresponding to the robotic medical procedure performed by using a robotic instrument on a patient within a population, and (ii) receiving a plurality of pretreatment data sets each defining one or more of the patient involved in the robotic medical procedure, the placement or operation of a medical device or robotic instrument, the pressure applied by the robotic instrument, or the timing of the steps of the robotic medical procedure; receiving or identifying object data defining one or more of the duration of the robotic medical procedure or the patient's outcome; identifying a pattern describing one or more of the timing of the steps of the robotic medical procedure or the patient's outcome to be achieved during the duration defined by the object data, the placement or operation of the patient, medical device, or robotic instrument involved in the robotic medical procedure, the pressure applied by the robotic instrument, over the plurality of pretreatment data sets; receiving information about the robotic medical procedure to be performed in the future on patients outside the population; automatically generating guidance for performing the robotic medical procedure, the guidance comprising the recommended placement or operation of the patient, medical device, or robotic instrument involved in the robotic medical procedure, the pressure applied by the robotic instrument, or the timing of the steps of the robotic medical procedure, based on an evaluation of the pattern identified over the plurality of pretreatment data sets and the information received about the robotic medical procedure to be performed; and generating and displaying an electronic screen of the guidance for performing the robotic medical procedure.

[0010] The memory medium may additionally or alternatively include one or more of the following features. That is, the period determined by the object data may be a part of the period of the robotic medical treatment, each previous treatment data set may include information collected by a robotic device associated with the robotic instrument during the corresponding robotic medical treatment process, the step of identifying the pattern may include identifying at least one occurrence level of the placement or movement of the patient, medical device, or robotic instrument across the plurality of previous treatment data sets, the step of identifying the pattern across the plurality of previous treatment data sets may include describing the operation of the robotic instrument in a part of the process of the robotic medical treatment achieved during the period determined by the object data, the period may be a period in a part of the process of the robotic medical treatment, the information about the robotic medical treatment to be implemented may include information about at least one of the patient, type of treatment, characteristics of the operating room, or the user's past experience, and the medical device may be a table for supporting the patient.

[0011] It will be understood that both the foregoing summary description and the following detailed description are for purposes of illustration only and do not limit the invention as claimed. The accompanying drawings, which form a part of this specification and are hereby incorporated by reference, illustrate exemplary embodiments of the invention and, together with the description, serve to explain the principles of the invention.

Brief Description of the Drawings

[0012]

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DETAILED DESCRIPTION OF THE INVENTION

[0013] The present invention is introduced into a system and method for providing guidance for the robotic medical treatment. In one embodiment, the treatment optimization device receives information corresponding to the input treatment. The information is then analyzed by the treatment optimization device to determine a pattern. The treatment optimization device further receives an input related to a robotic medical treatment for which the treatment optimization device is to generate guidance. The treatment optimization device generates guidance based on the pattern and information related to the robotic medical treatment to assist in the execution of the robotic medical treatment.

[0014] (Exemplary embodiment) FIG. 1 shows a system 2 for generating guidance for the robotic medical procedure, and FIG. 2 shows a method for generating guidance. The system 2 includes a treatment optimization device 10. The treatment optimization device 10 can receive input treatment data 4 from a plurality of robotic systems 5 (FIG. 2, step 210). In one embodiment, each set of input treatment data 4 corresponds to a completed or ongoing robotic medical procedure performed by a user using the robotic system 5. As used herein, "user" is synonymous with "practitioner" and may be any person (e.g., surgeon, technician, nurse, etc.) who completes the described act. Among the several components, each of the robotic systems 5 may include a robotic device, a guidance module, and a camera stand for tracking patients and other objects. The guidance module and the camera stand (referred to herein as the guidance component 24) may include a screen for providing an output to the user. One or more of the robotic device, the guidance module, or the camera stand may store the input treatment data 4 that can be retrieved by the treatment optimization device 10. Alternatively, the input treatment data 4 may be stored in any other component of the robotic system 5, or may be stored external to the robotic system 5. The stored input treatment data 4 may be analyzed by the treatment optimization device 10 to determine a pattern of characteristics of the corresponding medical procedure (FIG. 2, step 220).

[0015] The treatment optimization device 10 further receives information about the robotic medical treatment to be supported (referred to as supported treatment information 6) (FIGS. 1 and 2, step 230). Next, the treatment optimization device 10 generates guidance for the supported treatment based on the analysis of the input data 4 and the supported treatment information 6 (FIGS. 1 and 2, step 240). In this specification, "supported treatment" refers to the robotic medical treatment to which the guidance from the treatment optimization device 10 relates. The term "supported treatment" is used in this specification to distinguish the treatment indicating the guidance, or the treatment related to the guidance, from the treatment used as an input to the treatment optimization device 10 and the corresponding data 4. The supported treatment may or may not have started or been completed when the guidance is generated or when the guidance is provided to the user. Further, the supported treatment may be a planned treatment that has not actually been executed, a partially completed treatment, or a treatment that has already been completed. The output provided by the treatment optimization device 10, which can be guidance related to the supported treatment, may or may not be actually performed by the user. If performed, the guidance may or may not actually optimize the treatment with respect to a given measurement criterion.

[0016] (Treatment Optimization Device) The treatment optimization device 10 can be utilized to execute various functions (e.g., calculation, processing, analysis) described in this specification. The treatment optimization device 10 may include a processing circuit 12 having a processing device 14 and a memory 16. The processing device 14 can be embodied as a general-purpose processor, an application-specific integrated circuit (ASIC), one or more field-programmable gate arrays (FPGAs), a group of processing components, or other suitable electronic processing components. The memory 16 (e.g., memory, memory unit, storage device, etc.) is one or more devices (e.g., RAM, ROM, flash memory, hard disk storage device, etc.) for storing at least one of data and computer code for completing or facilitating the various processes described in this specification. The memory 16 may be a volatile memory or a non-volatile memory, or may include a volatile memory or a non-volatile memory. The memory 16 may include a database component, an object code component, a script component, or any other type of information structure for supporting the various acts described in this specification. According to an exemplary embodiment, the memory 16 may be communicatively connected to the processing device 14 and may further include computer code for executing one or more processes described in this specification. The memory 16 may include various modules capable of storing at least one of data and computer code related to a specific type of function. In one embodiment, the memory 16 includes several modules related to medical treatment, such as an input module 18, an analysis module 20, and an output module 22.

[0017] It should be understood that the treatment optimization device 10 does not need to be housed in a single housing. Rather, the components of the treatment optimization device 10 may be arranged in various configurations of the system 2 illustrated in FIG. 1 or may be located remotely. The components of the treatment optimization device 10, including the components of the processing device 14 and the memory 16, may be arranged, for example, in the components of different robotic systems 5 or in the robotic system components for assisting treatment (e.g., the guidance component 24).

[0018] The present invention contemplates a method, a system, and a program product in any machine-readable medium for performing various operations. The machine-readable medium may be part of the treatment optimization device 10 or may be connected to the treatment optimization device 10. Embodiments of the present invention may be embodied by using an existing computer processing device or by a dedicated computer processing device for an appropriate system incorporated for this or other purposes, or by a hardwired system. Embodiments included in the present invention include a program product comprising a machine-readable medium for storing, holding, or having machine-executable instructions or data structures. Such a machine-readable medium may be any available medium that can be accessed by a general-purpose or dedicated computer or other machine with an associated processing device. By way of example, such a machine-readable medium may be RAM, ROM, EPROM, EEPROM, CD-ROM or other optical disk storage device, magnetic disk storage device, other magnetic storage device, solid state drive, or any other medium that can be used to hold or store the desired program code in the form of machine-executable instructions or data structures and can be accessed by a general-purpose or dedicated computer or other machine with an associated processing device. When information is transferred or provided to a machine via a network or other communication connection (either wired, wireless, or a combination of wired or wireless), the machine appropriately regards the connection as a machine-readable medium. Accordingly, any such connection is appropriately termed a machine-readable medium. Combinations of the above are also included within the scope of machine-readable media. Machine-executable instructions include, for example, instructions and data that cause a general-purpose computer, a dedicated computer, or a dedicated processing machine to perform a particular function or a combination of functions.

[0019] Referring again to FIG. 1, the treatment optimization device 10 further includes one or more communication interfaces 28. The communication interface 28 can be a wired or wireless interface (such as a jack, antenna, transmitter, receiver, transceiver, wire terminal, etc.) for performing data communication with an external source via a direct connection or a network connection (such as an Internet connection, LAN, WAN, or WLAN connection), or may include such an interface. For example, the communication interface 28 may include an Ethernet card and ports for transmitting and receiving data via a communication link or network based on Ethernet (registered trademark). In other examples, the communication interface 28 may include a Wi-Fi (registered trademark) transceiver for communication via a wireless communication network. Thus, when the treatment optimization device 10 is physically separated from other components of the system 2 shown in FIG. 1, such as the robot system 5, the original arrangement of the support treatment information 6, or the components of the support treatment, the communication interface 28 can enable wireless communication between the treatment optimization device 10 and these separated components.

[0020] (Input treatment data) The input treatment data 4 is data corresponding to a robotic medical treatment implemented using the robot system 5. The data 4 may be related to any characteristic of the corresponding input treatment. Referring to FIG. 5, the input treatment data 4 may include, for example, patient information (e.g., biometrics, patient images, coexisting diseases, allergies, etc.), characteristics of the operating room (e.g., scale, setup), preoperative information (e.g., surgical plan, type of treatment), intraoperative information (e.g., treatment actions, time required for specific steps of the treatment), postoperative information (e.g., final placement of any implant), and at least any one of information related to any device used in the process of the treatment such as a robot. The data 4 may be input into the robot system 5 before the treatment (e.g., manually by a user or by any form of data transfer), or may be collected, measured, recorded, or acquired by the robot system 5 during the treatment process. Robot data refers to any data 4 that is input into, recorded by, or collected and acquired by a robot device in relation to a medical treatment implemented using the robot device. The input treatment data 4 corresponding to the treatment may include a log file in addition to other data corresponding to the treatment, but the data acquired during the treatment process may be in the form of a log file. In one embodiment, the set of input treatment data 4 corresponds to one medical treatment implemented using the robot system 5.

[0021] Referring to step 210 in FIGS. 1 and 2, treatment optimization device 10 may receive any number of sets of input treatment data 4, where each set corresponds to a medical treatment. In one embodiment, treatment optimization device 10 may receive sets of input treatment data 4 from several robot systems 5, along with a significant number of sets collected from each respective robot system 5. Each set of input treatment data 4 collected from a single robot system 5 may correspond to different treatments performed using that robot system 5. In other embodiments, the medical treatments corresponding to the sets of input treatment data 4 received by treatment optimization device 10 may all be performed using the same robot system 5, or each of the medical treatments may be performed using a different robot system 5.

[0022] The input treatment data 4 received by treatment optimization device 10 may include information indicating the characteristics of the corresponding input treatment. For example, input treatment data 4 from a particular treatment may, among many characteristics, indicate bone shaping, or the skill of the operator for performing other parts of the treatment, the time required for a particular part of the treatment, the pressing force on the bone during a certain process of the treatment, or the configuration of a particular component of the robot system or the placement during a human treatment process.

[0023] The input treatment data 4 may indicate the skill of the operator for bone shaping, for example, by including log lines related to the placement and orientation of surgical instruments over time. The robotic system 5 may include a tracking system that monitors the position and orientation of the patient and the robotic device including the surgical instrument during the treatment process. Data 4 regarding the position and orientation of various components may be stored in a log file provided in any component of the robotic system 5, such as the robotic device, the guidance module, or the camera stand of the tracking system. A log file having data 4 indicating the position and orientation of the instrument during the treatment process is received by the treatment optimization device 10 (for example, by executing instructions included in the input module 18 of the memory 16), and further, may be analyzed by the treatment optimization device 10 (for example, by executing instructions included in the analysis module 20 of the memory 16) to determine how the operator executed a particular part of the treatment.

[0024] In one example, the position and orientation data may indicate that the operator swung the instrument left and right to complete a particular part of the treatment. However, log files from different treatments may include data 4 indicating that the operator penetrated the surgical instrument into the bone several times instead of swinging the instrument left and right to complete the same part of the treatment. Thus, each set of input treatment data 4 may indicate characteristics of the corresponding treatment, such as the skill of the operator during a particular part of the treatment process.

[0025] In a second example, the input treatment data 4 may include information indicating the manner in which the operator has completed a pre-operative range of motion test. For example, in knee surgery, different operators may use different techniques to map the patient's range of motion. The input treatment data 4 may include log lines that describe the position and orientation of the tibia and femur during the corresponding treatment's range of motion test. The position and orientation data can be analyzed to determine the manner of treatment applied to the tibia and femur by the operator during the range of motion test. Data 4 from various treatments can be compared to determine the manner in which different operators have completed a similar range of motion test, or to determine whether a single operator has used the same technique during different treatment procedures.

[0026] In other examples, the input treatment data 4 may include information indicating the length of time for a particular part of the treatment. A number of tasks can be performed during the course of a treatment. For example, in knee replacement surgery, the tasks can include the aforementioned pre-operative range of motion test, the femur preparation which may include using different instruments for cutting, carving, or other shaping of the femur, the tibia preparation which may include using different instruments for cutting, carving, or other shaping of the tibia in a similar manner as the femur preparation, and the implant placement. Analysis of the input treatment data 4 may indicate the time required for each part and sub-part of the treatment. For example, the data 4 may indicate the overall length of time for femur preparation, or the length of time to complete the cutting of one bone.

[0027] In yet another embodiment, the input treatment data 4 may indicate the pressing force on the bone during a part of the corresponding treatment. In this embodiment, the robotic device may include a force sensor, and information regarding the readings of the force sensor may be stored in a log file. The data 4 of the log file may then be analyzed to track the pressing force on the bone (e.g., by a surgical instrument) during the course of the treatment.

[0028] The tracking system used during the treatment process can respond in relation to the arrangement of various components in the operating room and generate data 4 that will be stored in a log file. For example, data 4 can indicate the robot device (including the surgical instrument and the base of the robot device), the guidance module, the patient's anatomical structure (e.g., femur, tibia), and the position of the tracking system camera over time, along with other items tracked by the tracking system. Data 4 can be analyzed to determine the arrangement of components during the treatment process.

[0029] (Data analysis) Referring to step 220 of FIG. 2, the input treatment data 4 received from the robot medical system 5 (or other arrangement) can be analyzed by the treatment optimization device 10 (e.g., by executing instructions stored in the analysis module 20). In one embodiment, data 4 may be analyzed to determine a pattern of characteristics across multiple input treatments. The analyzed characteristics can be related to the skill of the operator, the length of a part of the treatment, the pressing force on the bone, the arrangement of objects or people during the treatment process, or any other characteristic that can be recognized by the analysis data corresponding to the robot medical treatment.

[0030] The analysis module 20 of the treatment optimization device 10 may include instructions for analyzing the input treatment data 4 initially included in a log file or other form to determine a pattern of one or more characteristics across multiple treatments. In certain embodiments, the analysis module 20 may process the log file using standard extraction, transformation, and loading procedures that convert a plain text file into a database record. The analysis module 20 may further include statistical analysis processing to determine patterns in the input treatment data 4.

[0031] The pattern of a characteristic may be a description of the overall occurrence (or lack of occurrence) of the characteristic, a particular feature of the characteristic, a factor related to the occurrence of the characteristic, or any other indication of the characteristic. For example, in the above example related to the left - right movement of a surgical instrument, the pattern may be that the technique related to the left - right movement is used in 75% of the procedures (e.g., seen in 75% of the log files where the left - right movement was analyzed). In another example, the pattern may be a curve mapping the distance the instrument was swung once during the course of the left - right movement among a plurality of procedures. Such a curve can provide information about the average distance when the instrument is swung. In yet another embodiment, the pattern may be that 80% of the practitioners using the technique related to the left - right movement did so with their left hand.

[0032] In other embodiments, the characteristic of interest may be the technique for completing a range - of - motion test. The pattern of the characteristic recognized by the treatment optimization device 10 may be, for example, that 30% of the practitioners use a first technique, 30% of the practitioners use a second technique, and 40% of the practitioners use a third technique. The pattern may additionally or alternatively identify the details of the implementation of each technique (e.g., where the leg was positioned during a particular stage of the test over a plurality of procedures), or the differences in the implementation of a particular technique among the practitioners. The pattern may additionally or alternatively identify other information related to each use of the technique (e.g., whether a particular practitioner uses a particular technique more often).

[0033] When the characteristic is time - related, the pattern may be the average length of time of a particular part of the treatment. In another embodiment, the pattern may be that using a particular technique for a task corresponds to a shorter completion time of the task. In yet another embodiment, the pattern may be that performing a set of tasks in a particular order results in a shorter overall completion time. The pattern of a characteristic may be any description of the characteristic generated by analyzing a plurality of treatments.

[0034] The pattern related to the pressing force on the bone may be the average force applied during a particular part of the procedure (e.g., the average force applied during a particular type of bone cutting measured over multiple procedure steps). In other embodiments, the pattern may be that a skilled practitioner uses a different force than a less experienced practitioner, that a particular technique corresponds to a greater or lesser application of force, or that a particular practitioner uses different force levels depending on the operating room setting.

[0035] In still other embodiments, the pattern may relate to the placement of the object or person during the procedure. The pattern may be, for example, that a particular operating room layout or scale typically determines a particular placement of the robotic device, patient table, camera stand, patient, and user. The pattern may additionally or alternatively be that a particular type of procedure is generally completed by having the robotic device placed at a particular position relative to the patient or other reference position, or that a particular practitioner generally completes the procedure by placing the object in a particular way in the operating room.

[0036] In short, the treatment optimization device 10 can analyze the data 4 to identify a pattern of any characteristic of interest. The pattern may be any other information that describes an occurrence, particular feature, embodiment, interrelated factors, or characteristic and that may be useful in the process of generating guidance for assisting with the treatment.

[0037] (Information for assisting treatment) Referring to step 230 of FIGS. 1 and 2, the treatment optimization device 10 may receive assistance treatment information 6 regarding the treatment that will be indicated by the generated guidance. The assistance treatment information 6 may be any information regarding the assistance treatment, including information about the patient of the assistance treatment. FIG. 3 shows some examples of the assistance treatment information 6 including patient information 30, information on the type of treatment 32, characteristics of the operating room 34, and information on the user's past experience 36. The assistance treatment information 6 may be provided in any form, such as an image (e.g., an image of the patient or the operating room), a data file, manual input by the user, or received from a patient monitoring device, and may further be transmitted to the treatment optimization device 10 via the communication interface 28.

[0038] The patient information 30 may include various characteristics of the patient of the assistance treatment, such as height, weight, body mass index, bone density, skeleton, cartilage thickness, etc. The patient information 30 may be manually input by the user, uploaded from an existing image or text file, received from a patient monitoring device, or communicated to the treatment optimization device 10 by any other method via the communication interface 28. The patient monitoring device may be, for example, a device that monitors the patient's nerve activity or heart activity.

[0039] The information on the type of treatment 32 may include a general type of the assistance treatment (e.g., total or partial knee replacement, hip replacement, ankle, shoulder, or spinal treatment, treatment on the bone outside the joint, or non-orthopedic treatment such as to soft tissue). The information 32 may additionally or alternatively include a surgical plan having details of the assistance treatment, such as the planned shape and sequence of osteoplasty, or instruments (e.g., saws, bars) used during the treatment process.

[0040] The characteristics 34 of the operating room may include the shape and scale of the operating room and the planned arrangement of various people and objects during the treatment process. For example, the surgical plan may indicate the initial arrangement of one or more of the patient table, the patient, the surgeon, other operating room personnel, the robotic device, the guidance module, the tracking system components, the instruments (e.g., retractors used during the treatment process, and other objects), or the wiring, piping, and other equipment. During the support treatment, the system 5 may track any of these components including a part of a person or an object (e.g., an arm) using one or more tracking systems.

[0041] Finally, the past experience 36 of the user may include information regarding the past experience of the user performing the robotic medical treatment. The information 36 may include general information about the number of treatments completed by the user (e.g., the user has never performed a robotic medical treatment, the user has performed it more than twice, or the user has performed many treatments), or may include detailed information about specific treatments completed by the user. The treatment optimization device 10 can consider the past experience of the user when generating guidance for the support treatment.

[0042] In one embodiment, the treatment optimization device 10 may receive further input in the form of rules. The rules may define the results and guidance that should result when the treatment optimization device 10 receives a specific input. For example, a rule may define that for a patient weighing more than 300 pounds (about 136.08 kg), the treatment optimization device 10 should not recommend an implant size smaller than a specific threshold. Similarly, in other examples, the rules may define that the treatment optimization device should not recommend a large implant exceeding a specific threshold for a patient with a fragile femur. The rules may be the principle for any part of the treatment or decision-making step.

[0043] The rules may be general rules applicable to many procedures, but since they may be applied to support procedures, they may be considered part of the support procedure information 6. The rules may be considered and applied by the treatment optimization device 10 when generating guidance. Similar to other support procedure information 6, the rules may be manually input by the user, uploaded from an existing image or text file, communicated to the treatment optimization device 10 by some other method via the communication interface 28, or further stored in the storage device 16. The generation of the rules can be done by manually reviewing the literature, analyzing the input treatment information 4 (manually or by the treatment optimization device 10), or by some other mechanism.

[0044] (Guidance) Referring to step 240 of FIGS. 1 and 2, the treatment optimization device 10 generates an output 26 by executing an algorithm stored in the output module 22. In one embodiment, the output may be guidance that an operator executes during the support procedure. The step of generating guidance may include generating updated robot instructions that cause the robot to provide guidance to the user during execution. The guidance may be displayed on a screen of one or more guidance components 24. The guidance may be based on a pattern of characteristics of the input treatment recognized by the treatment optimization device 10 and the support treatment information 6 received by the treatment optimization device 10.

[0045] FIG. 4 shows some exemplary types of guidance that may be generated by the treatment optimization device 10. The divisions shown in FIG. 4 and the examples provided below are merely illustrative. A particular type of guidance may be applicable to multiple divisions or incorporated into divisions other than those shown in FIG. 4. In one example, the guidance relates to clinical decision support 40. Clinical decision support 40 may include any type of guidance intended to assist an operator in making decisions before, during, or after a robotic surgical procedure.

[0046] In one embodiment, the guidance assists the operator in making decisions regarding the movement 42 of the instrument. The guidance may recommend the left and right movements of the instrument in order to complete a specific part of the procedure. This recommendation may be based on the pattern recognized by 75% of the operators performing the left and right movements as described above. Alternatively, the guidance may be based on any other pattern recognized by the treatment optimization device. The guidance may also be in accordance with a specific support treatment based on the support treatment information. Thus, when a specific piece of information included in the support treatment information 6 is very disadvantageous for recommending left and right movements (for example, it is more difficult to perform left and right movements and the user is inexperienced), the treatment optimization device 10 will take this into account and recommend different techniques. In this approach, the treatment optimization device 10 may integrate the data from the input treatment and the information about the support treatment in order to generate appropriate guidance targeted for the support treatment.

[0047] In another example, the treatment optimization device 10 may generate guidance regarding implant type 44 (e.g., an implant or a component of an implant used in knee or hip replacement surgery), or regarding implant placement. The implant type 44 may be the size of the implant, the brand of the implant, the material of the implant, or any other characteristic regarding the implant. The recommendation regarding the implant type 44 may be based on the recognized pattern of the type of implant used for the patient of the input treatment. For example, the guidance may be based on the type of implant that is typically selected for patients having a bone size and skeleton similar to that of the patient of the assist treatment. In another example, the implant type 44 may be based on the type of implant selected for other patients having a weight similar to that of the patient of the assist treatment. Thus, the generation of guidance related to the implant type 44 may be based on the pattern recognized in the data of the input treatment and information for the patient of the assist treatment. Similarly, the guidance related to the position of the implant may be based on the recognized pattern of the placement of the implant in previous treatments made for patients having characteristics (e.g., bone size, skeleton, weight) similar to those of the patient of the assist treatment. In one embodiment, the treatment optimization device 10 may receive information regarding the long-term outcome of the patient of the input treatment as part of the input treatment data 4. The treatment optimization device 10 may base at least part of the type or placement of the implant that has provided the best long-term outcome for the patient of the input treatment on the guidance for the assist treatment.

[0048] In some examples, the pattern of characteristics and the information of the assist treatment may relate to the same type of information (e.g., the skeleton of the patient of the input treatment and the skeleton of the patient of the assist treatment), but in other embodiments, the pattern and the information of the assist treatment may relate to different types of information. For example, the guidance regarding the implant type 44 is based on the pattern in which a specific type of input treatment (e.g., unicompartmental knee replacement surgery) typically uses a specific type of implant and the information of the assist treatment regarding the patient's skeleton.

[0049] In other examples, the guidance may relate to the bone shaping sequence 46. The treatment optimization device 10 may recognize that an operator of an input treatment of the same type as the assistance treatment usually performs bone shaping in a specific sequence. Thus, the treatment optimization device 10 may generate guidance that recommends that the operator of the assistance treatment perform bone shaping in a similar sequence. However, if other factors, such as the patient's skeleton of the assistance treatment and further the characteristics of the operating room (e.g., the initial arrangement of the robotic device), are disadvantageous to performing shaping in the same sequence as the input treatment, the treatment optimization device 10 may recommend another sequence of bone shaping.

[0050] Another type of clinical decision-making support guidance may be user-specific guidance 48. The user-specific guidance 48 can be any type of guidance that takes into account the experience, qualifications, or other characteristics of the operator of the assistance treatment. The user-specific guidance 48 may consider information such as, for example, the number of robotic surgical procedures the operator has previously completed, the techniques the operator used to complete those surgical procedures, the operator's dominant hand, or the operator's preferences. Such information about the operator may be included in the assistance treatment information 6 or may be included in the input treatment data 4 corresponding to the treatment completed by the operator.

[0051] In one embodiment of user-specific guidance, the treatment optimization device 10 may output different orders or numbers of guidance steps for practitioners with different levels of experience. For example, while a treatment is being performed by a less experienced practitioner, the treatment optimization device 10 may provide a larger number of surgical steps, including being more detailed, than when provided to a more experienced practitioner. In this way, a more experienced practitioner can receive a more simplified guidance appropriate to the practitioner's experience during the treatment process. Over time, as a novice practitioner gains more experience, the treatment optimization device 10 may reduce the number of at least one of the details and steps shown to the practitioner during the treatment of that practitioner. Similarly, in other embodiments, the treatment optimization device 10 may display a specific message to a novice practitioner that is not necessarily displayed to a more experienced practitioner. For example, a relevant warning message (e.g., an often-occurring but undesirable action) may be displayed during the treatment for a novice practitioner. As the practitioner gains more experience and stops performing undesirable actions, the treatment optimization device 10 stops displaying the message. On the other hand, if a particular user with experience may benefit from the message (e.g., because the user is performing a particular undesirable action during the treatment or has performed an undesirable action during a past treatment), the treatment optimization device may display the message for that user.

[0052] Another category of the guidance may include an operating room guidance 50. This type of guidance may also relate to the placement of objects or people within the operating room. The equipment placement guidance 52 may be a recommendation regarding the placement of a robotic device, a guidance module, a tracking system, a patient table, or any other object within the operating room in a particular placement. The recommendation may be based on the placement of these items in input procedures having similar operating room characteristics (e.g., size, shape), and may also take into account fixed objects or other constraints of the operating room used for the assistance procedure. For example, some operating rooms may have a patient table fixed to the floor. Therefore, the recommendation regarding the placement of the remaining objects may be based on the placement of the fixed patient table in addition to the pattern of object placement during the input procedure.

[0053] The guidance regarding the patient placement 54 may recommend that the user place the patient in a particular direction, and more specifically, may be related to the particular placement of the patient's legs or other parts of the anatomical structure. For example, if in a previous procedure having operating room characteristics similar to the operating room characteristics 34 of the assistance procedure, the patient was placed facing a particular direction with respect to the robotic device, the guidance may recommend that the patient be placed similarly with respect to the robotic device used in the assistance procedure. Similarly, if the patient's legs were placed at a particular angle at the knees at the start of most input procedures having characteristics similar to the assistance procedure, the guidance may recommend placing the patient's knees at a predetermined angle at the start of the assistance procedure.

[0054] In another embodiment, the output guidance 26 may be a recommendation regarding the user placement 56. The user may be an operator of the robotic device or any other worker in the operating room (e.g., technician, assistant, doctor, nurse, etc.). The guidance regarding the user placement 56 may be based on the pattern of the user placement recognized from the input treatment data 4 and the support treatment information 6 (e.g., type of treatment 32, characteristics of the operating room 34, etc.). Analysis of the input treatment data 4 may reveal that when the user stands in a specific placement with respect to the patient and the robotic device, a particular type of treatment can be completed more urgently. Thus, for support treatments with similar characteristics, the guidance 26 may recommend that the user stand in a similar position with respect to the patient and the robotic device to perform the treatment.

[0055] (Exemplary workflow) FIG. 5 shows an exemplary workflow for providing guidance based on the pattern in the input treatment data 4. Step 510 in FIG. 5 includes the input treatment data 4 that may be received by the treatment optimization device 10. As described above, the input treatment data 4 may include information about the patient received by any method, information about the operating room (OR) (e.g., size of the OR, setup of the OR), pre-operative information (e.g., range of the exercise test described above, treatments to be performed before the operation), intra-operative information (e.g., tracking information, placement of the bones contacted for bone registration), post-operative information (e.g., desired final implant placement, information from rehabilitation), and information about the surgical robot (e.g., joint angles, tolerances, whether the robot accurately performed its movement during the treatment), and information about any other devices or equipment used during the treatment, and may include at least any one of any information about the robotic medical treatment.

[0056] The processing data shown in step 520 may include information resulting from the analysis of the raw data of the case in step 510, or may be derived from the raw data of the case shown in step 510. The processing data may include values that are comparable between two or more treatments and may assist in the determination of trend data in step 530. For example, the processing data may include information regarding the efficiency of the operating room (e.g., the degree to which the OR staff completed the treatment quickly). Information regarding efficiency may be derived from raw data related to various types of cases, such as intraoperative data related to the time at each part of the treatment during surgery, or robot data related to the operation of the robot. The processing data may further include information regarding the actions of the surgeon (e.g., how the surgeon holds a particular instrument). Information regarding the actions of the surgeon may be derived from at least any one of preoperative data, intraoperative data, and robot data, for example, by comparing the preoperative plan with the tracking data obtained during surgery and the information regarding the operation of the robot acquired during the process of the treatment. The step accuracy (e.g., how accurately the surgeon or OR staff completed the steps of the treatment) may be similarly derived from comparing preoperative information with intraoperative information. Information regarding the patient's outcome may include a comparison between preoperative data and postoperative data. Finally, information regarding the condition of the robot (or the condition of other devices or apparatuses used during the process of the treatment), such as information regarding whether robot parts need to be replaced, information for determining the usage history of the motor, or information for determining whether maintenance is required for other instruments, may be derived from the raw data of the case related to the robot or other devices.

[0057] By reconsidering input treatment data 4 and processing data from at least any one of a plurality of treatments, surgeons, operating rooms, hospitals, and regions, treatment optimization device 10 can determine trend data in step 530. The trend data may include patterns recognized by treatment optimization device 10. Examples of trend data include surgeon techniques (e.g., different techniques being used in different regions or hospitals, different surgeons using different techniques), case reports (e.g., summaries of numerous different treatments including information about the treatment such as bone alignment accuracy, comparison of pre-operative planning and post-operative outcomes, etc.), population health (e.g., patients in different regions or hospitals having better or different outcomes, patients undergoing a particular treatment having better or different outcomes), OR practices (e.g., a particular OR setting, staff, or treatment result leading to better or different outcomes), institutional effectiveness (e.g., how well the user performs the steps of the treatment, how well an institution (e.g., a button) functions), and maintenance schedule (e.g., whether the trend data indicates that a particular robotic device or other device requires maintenance due to a change in the outcome of the treatment or because the devices have performed a certain number of treatments).

[0058] In step 540, the trend data obtained in step 530 can be applied in various settings and moreover can be provided to many customers to provide guidance to the customers. For example, to provide guidance to a surgeon, information about patients and surgeries (e.g., pre-operative, intra-operative, and post-operative) can be processed to determine surgeon actions (e.g., goodness of implant placement), step accuracy (e.g., goodness of the surgeon's bone alignment work), and patient outcomes. The surgeon can also receive case reports that summarize information about various treatments. Based on the information in the case reports, treatment optimization device 10 may provide guidance to the surgeon to improve future treatments.

[0059] In another example, the treatment optimization device 10 may provide guidance to institutions such as hospitals, insurance companies, or governments. For example, a hospital may be interested in various trend data, including data related to a surgeon's skills or maintenance schedule. In one example, a pattern related to the maintenance schedule may indicate an excessive frequency of maintenance that may suggest that the hospital should further investigate the equipment.

[0060] Furthermore, the systems and methods described herein may be used by a hospital to optimize at least one of the human composition and schedule of an OR. In one example, the input treatment data 4 may include information related to the staff's duties during the corresponding medical treatment (e.g., name, caseload, personal history, experience, etc.). In a particular case, the placement of each staff member may be tracked by using a navigation system during the treatment process. The trend data may include patterns related to the staff composition of the treatment and the patient's outcome. These trends may allow the treatment optimization device 10 to provide guidance assigned to a specific person for a specific treatment. The treatment optimization device 10 may further receive information related to at least one of one or more surgeons and the surgical schedule of the operating room. The surgical schedule may assist the treatment optimization device 10 in recommending specific personnel for a specific treatment. For example, for a complex case, the treatment optimization device 10 may recommend at least one of a person who has experience in the treatment and has performed surgeries on patients with good clinical results, a person who has been too busy (e.g., overloaded) in the past few days, and a person who is available for surgery during the schedule or desired time period (e.g., in the morning). In one example, the treatment optimization device 10 can recommend setting up a robot for the first OR staff team and may recommend performing a timeout procedure (e.g., rechecking the patient, treatment, and other details prior to the surgical procedure) for the second OR staff team.

[0061] In another example, the treatment optimization device 10 may be linked to the hospital's alarm system in order to optimize the use and scheduling of the OR. For example, if an OR staff member does not appear for a scheduled procedure, the treatment optimization device 10 may send an alarm to the hospital's scheduling system. In another example, if a scheduled surgeon typically takes a long time to perform a procedure, the treatment optimization device 10 may send an alarm to the hospital's scheduling system in order to enable proper planning and subsequent scheduling of the procedure. In yet another example, an alarm may be sent if a surgeon takes longer than scheduled during the course of a procedure.

[0062] The robotic system 5 may include a tracking method that can be useful in inventory tracking and billing. In one example, the treatment optimization device 10 may receive information regarding implants and other inventory used during the course of a medical treatment (e.g., implant part number or type, price, available quantity, or quantity used during the course of a treatment). In some prior art systems, personnel may track inventory and a manually based tracking invoice may be submitted by the device manufacturer to the hospital. In one example, the robotic system 5 may include an identification device for implants or other devices and instruments, such as a barcode scanner, or other visual or wireless recognition system, to verify the usage status of components (e.g., by scanning the packaging). This information may further be used to automatically generate and export an electronic surgical sheet to facilitate the billing process. The electronic surgical sheet may provide a dynamic record of the hospital's inventory consumption. Inventory tracking may also be useful for keeping track of disposable OR items, such as surgical sponges.

[0063] Referring again to FIG. 5, the surety company is interested in population health to assist in setting the surety rate. The government is interested in population health, for example, for surveys or policy development. Population health may be determined by analyzing patient data, pre-operative information, and post-operative information for a plurality of patients to determine the outcome of the patient.

[0064] The systems and methods for generating the guidance described herein may be used by an operator in training. Trend data may be provided to the device manufacturer, the surgeon, or any other personnel for training purposes. Trends regarding the surgeon's technique and OR practices can be particularly useful for training. For example, training regarding the surgeon's technique may advise the surgeon not to hold the probe in a particular position. In another example, the training may include suggestions for positioning the OR camera in a particular arrangement.

[0065] Analysis of data from numerous prior procedures may shed light on general best practices (e.g., techniques, equipment, and user placement) that can be provided to the operator before or during a robotic procedure or during other training sessions. The best practice guidance may be extracted by the treatment optimization device 10 during analysis of the input treatment information 4 or received by the treatment optimization device 10 in the form of rules or other inputs. Providing guidance to the operator in best practice can accelerate the learning process for the operator using the robotic system 5.

[0066] The systems and methods described herein may further be used to fine-tune a practitioner's technique by comparing input treatment data 4 from other practitioners to input treatment data 4 from the practitioner's own past treatments. For example, the treatment optimization device 10 may recognize that a particular change in a practitioner's technique can shorten the overall length of a treatment and provide this guidance to the practitioner. In this example, the guidance provided to a trainee may be user-specific guidance 48 in a form that supports clinical decision-making, the "assisted treatment" may be a future treatment to be performed by the practitioner, and the assisted treatment information 6 may be information about the practitioner. In one embodiment, the guidance provided to the practitioner may be a recommendation to watch a training video. For example, the treatment optimization device 10 may recognize that a practitioner takes longer than other users to complete a particular stage of a treatment and may recommend a training video about the technique to shorten the completion time.

[0067] Trend data may further be provided to the team of the device manufacturer (e.g., of a device used in a medical treatment related to the input treatment data 4). For example, the manufacturer's sales and marketing team is interested in trends related to at least one of population health and OR practice. Knowledge of these trends can assist the sales and marketing team in at least one of selling medical devices and advising hospital staff on how to use the medical devices. The manufacturer's engineering team is interested in the effectiveness of at least one of a surgeon's technique and mechanism to assist in design improvements to at least one of the device's software and hardware. Finally, the service team is interested in trends in maintenance schedules to assist in efforts to reduce maintenance.

[0068] Although the principles of the present invention are described herein with reference to exemplary embodiments for particular applications, it should be understood that the disclosure is not limited thereto. Persons having ordinary skill in the art and being able to utilize the disclosure provided herein may recognize equivalent additional variations, applications, embodiments, and alternatives that all fall within the scope of the embodiments described herein. Accordingly, the present invention is not to be construed as limited by the foregoing description.

Claims

1. A method executed by a computer for generating and displaying a guidance screen for performing a robotic medical procedure in order to assist in the execution of the robotic medical procedure, comprising: receiving, by one or more processing devices from a plurality of robotic systems, input treatment data including a plurality of prior treatment data sets, each prior treatment data set corresponding to an instance of a robotic medical procedure performed on a patient within a population by using a robotic system including a robotic instrument and an electronic screen, defining one or more of the placement or operation of the robotic instrument involved in the instance of the robotic medical procedure performed, and including an indication of whether the robotic instrument accurately performed the robotic medical procedure during the course of the instance of the robotic medical procedure performed; receiving, by the one or more processing devices, from one or more data files, information about instances of robotic medical procedures to be performed in the future for patients outside the population, the information about instances of robotic medical procedures to be performed in the future for patients outside the population including preoperative data including data regarding patient outcomes and data regarding the duration of robotic medical procedures for patients within the population; determining, by the one or more processing devices executing data analysis of the input treatment data, a pattern of one or more characteristics, the pattern of one or more characteristics including (i) the placement or operation of the robotic system involved in the instance of the robotic medical procedure to be performed in the future for patients outside the population, or (ii) the pressing force on the bone measured by a force sensor included in the robotic instrument involved in the instance of the robotic medical procedure to be performed in the future for patients outside the population; automatically generating, by the one or more processing devices, guidance for performing an instance of a robotic medical procedure to be performed in the future using the robotic system, the guidance including recommended operations for the robotic instrument to complete a part of the robotic medical procedure; displaying, by the one or more processing devices, the guidance for performing an instance of a robotic medical procedure to be performed in the future on a first electronic screen; and a method comprising the steps of.

2. The method according to claim 1, wherein determining a pattern of one or more characteristics further comprises (iii) describing, in the case of the robotic medical treatment to be performed, the operation of the robotic system for a period defined by the pre-operative data or to achieve the patient outcome in the case of the robotic medical treatment to be performed.

3. The method according to claim 1, wherein the information about the case of the robotic medical treatment to be performed includes information about at least one of a patient outside the population, the type of treatment, or the characteristics of the operating room.

4. The method according to claim 1, wherein the guidance includes (i) the recommended timing of the steps of the robotic medical treatment in which the robotic system is involved, and (ii) the recommended order of the steps of the robotic medical treatment.

5. A non-transitory computer-readable storage medium that, when executed by a processing device, causes the processing device to perform a method for generating and displaying a guidance screen for performing a robotic medical treatment to assist in the execution of the robotic medical treatment, the method comprising: receiving, by one or more processing devices from a plurality of robotic systems, input treatment data including a plurality of prior treatment data sets, each prior treatment data set corresponding to a case of a robotic medical treatment performed on a patient within a population by using a robotic system including a robotic instrument and an electronic screen, defining one or more of the placement or operation of the robotic instrument involved in the case of the robotic medical treatment performed, and including an indication of whether the robotic instrument accurately performed the robotic medical treatment during the course of the case of the robotic medical treatment performed; receiving, by the one or more processing devices, from one or more data files, information about a case of a robotic medical treatment to be performed in the future for a patient outside the population, the information about the case of the robotic medical treatment to be performed in the future for a patient outside the population including pre-operative data including data regarding the patient outcome and data regarding the duration of the robotic medical treatment of patients within the population; A step of determining a pattern of one or more characteristics by the one or more processing devices that perform data analysis of the input processing data, wherein the pattern of the one or more characteristics is (i) the arrangement or operation of the robotic system involved in cases of the robotic medical treatment to be performed in the future for patients other than the population, or (ii) the pressing force on the bone measured by a force sensor included in the robotic instrument involved in cases of the robotic medical treatment to be performed in the future for patients other than the population, the step comprising: A step of automatically generating guidance for performing cases of robotic medical treatment to be performed in the future using the robotic system by the one or more processing devices, the guidance including operations recommended for the robotic instrument to complete a part of the robotic medical treatment, the step comprising: A step of displaying, on a first electronic screen, the guidance for performing cases of robotic medical treatment to be performed in the future by the one or more processing devices A non-transitory computer-readable storage medium comprising: **Claim 6** The storage medium according to claim 5, wherein each prior treatment data set includes information collected by a robotic system associated with a robotic instrument during the process of a corresponding case of a performed robotic medical treatment. **Claim 7** The storage medium according to claim 5, wherein the step of determining the pattern of the one or more characteristics further includes describing the operation of the robotic instrument during the process of a case of robotic medical treatment to be performed that achieves the period determined by the pre-operative data or achieves the patient's outcome. **Claim 8** The storage medium according to claim 5, wherein the information about the robotic medical treatment to be performed includes information about at least one of patients other than the population, the type of treatment, or the characteristics of the operating room. **Claim 9** The storage medium according to claim 5, wherein each prior treatment data set includes information related to the position or operation of the robotic system. **Claim 10** The method according to claim 1, wherein the patient's outcome is comparing the pre-operative data with the post-operative data.

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