Surgical devices, systems, and methods including adaptive control

Abstract

A surgical system with adaptive control includes a surgical cutting device, at least one sensor, and a controller. The surgical cutting device includes a cutting tool and a motor configured to drive movement of the cutting tool. The at least one sensor is configured to generate sensor data indicative of at least one characteristic of the surgical cutting device during use. The controller is configured to receive the sensor data and determine a performance condition of the surgical cutting device based at least on the sensor data. The controller is further configured to at least one of adjust a setting of the surgical cutting device or recommend a change related to use of the surgical cutting device when the determined performance condition is an adverse performance condition.

Description

Technical Field

[0001] This disclosure relates to surgical apparatus, systems, and methods, and more specifically to surgical apparatus, systems, and methods including adaptive control. Background Technology

[0002] Powered surgical cutting devices and systems are used in a variety of surgical procedures to perform a wide range of surgical cutting functions, including, for example, drilling, tapping, removing, dissecting, debridement, scraping, sawing, pulverizing and / or shaping of anatomical tissues including bone.

[0003] Many such powered surgical cutting devices and systems are precisely designed to ensure safe and effective operation. However, regardless of the precision of the design, conditions may arise during use that lead to unstable performance, loss of stability, reduced efficiency or effectiveness, and / or other adverse conditions. Summary of the Invention

[0004] As used herein, the term "distal" refers to the portion described as being farther from the operator (whether a human surgeon or a surgical robot), while the term "proximal" refers to the portion described as being closer to the operator. As used herein, terms including "usually," "about," and "substantially" are intended to cover variations up to and including ±10% (or greater, depending on industry standards) such as manufacturing tolerances, material tolerances, usage and environmental tolerances, measurement variations, design variations, and / or other variations. To the extent consistent, any aspect of the aspects described herein may be used in conjunction with any or all other aspects described herein.

[0005] According to various aspects of this disclosure, a surgical system with adaptive control is provided. The surgical system includes a surgical cutting device, at least one sensor, and a controller. The surgical cutting device includes a cutting tool and a motor configured to drive movement of the cutting tool. The at least one sensor is configured to generate sensor data indicative of at least one characteristic of the surgical cutting device during use. The controller is configured to receive the sensor data and determine, at least based on the sensor data, the performance conditions of the surgical cutting device. The controller is further configured to, if the determined performance conditions are unfavorable, perform at least one of the following: adjust the settings of the surgical cutting device or recommend changes related to the use of the surgical cutting device.

[0006] In one aspect of this disclosure, the controller is further configured to receive additional data and determine the performance condition based at least on the sensor data and the additional data. In various aspects, the additional data may include identification data, patient data, and / or procedural data.

[0007] In another aspect of this disclosure, the determined performance conditions include at least one of stability conditions or efficiency conditions. Additionally or alternatively, the determined performance conditions may be binary-defined or scaled-defined.

[0008] In another aspect of this disclosure, the controller is configured to adjust the settings of the surgical cutting device by adjusting at least one of the following when the determined performance conditions are unfavorable: the speed of the motor; the torque of the motor; the operating mode; or performance-influencing components, such as the damping components of the surgical cutting device (e.g., the positioning, characteristics, etc. of the damping components or other performance-influencing components).

[0009] In another aspect of this disclosure, the controller is configured to recommend changes related to the use of the surgical cutting device when the determined performance conditions are unfavorable performance conditions by recommending the following: changes to the ergonomic positioning of the surgical cutting device, changes to the technology, manual changes to performance-affecting components (such as damping components) (e.g., the positioning, characteristics, etc. of the damping components or other performance-affecting components); or changes to a different surgical cutting device or a portion thereof.

[0010] In another aspect of this disclosure, the at least one sensor includes at least one of the following: a vibration sensor, a positioning sensor, an acceleration sensor, an optical sensor, an audio sensor, a force sensor, a temperature sensor, and / or a motor electrical characteristic sensor.

[0011] In another aspect of this disclosure, the surgical cutting device also includes a handle and a shaft assembly, the handle housing the motor therein, and the shaft assembly being coupled to the handle and including an outer sleeve. In this aspect, the cutting tool extends through the outer sleeve of the shaft assembly. In these aspects, the at least one sensor is disposed on or within at least one of the following: the handle, the outer sleeve, or the cutting tool.

[0012] In another aspect of this disclosure, the controller is configured to operate in near real-time, for example, to determine the performance conditions and, if the determined performance conditions are unfavorable, to perform at least one of the following: adjustment or recommendation.

[0013] In another aspect of this disclosure, the surgical system includes a console configured to supply power and control signals to the surgical cutting apparatus. In this aspect, the controller is disposed within the console.

[0014] In another aspect of this disclosure, the controller is configured to implement at least one machine learning algorithm to determine the performance conditions.

[0015] An adaptive control method for a surgical system according to the present disclosure includes: driving a motor to move a cutting tool of a surgical cutting device to cut tissue; during the cutting of the tissue, monitoring sensor data indicating at least one characteristic of the surgical cutting device; determining performance conditions of the surgical cutting device based at least on the sensor data; and when the determined performance conditions are unfavorable performance conditions, performing at least one of the following: adjusting the settings of the surgical cutting device or recommending changes related to the use of the surgical cutting device.

[0016] In one aspect of this disclosure, the method further includes receiving other data, including at least one of the following: identification data, patient data, or procedural data. In such an aspect, the performance conditions are determined at least based on the sensor data and the other data.

[0017] In another aspect of this disclosure, the determined performance conditions include at least one of stability conditions or efficiency conditions.

[0018] In another aspect of this disclosure, when the determined performance conditions are unfavorable, the settings of the surgical cutting device are adjusted by adjusting at least one of the following: the speed of the motor; the torque of the motor; the operating mode; or performance-influencing components, such as the damping components of the surgical cutting device (e.g., the positioning, characteristics, etc. of the damping components or other performance-influencing components).

[0019] In another aspect of this disclosure, when the determined performance conditions are unfavorable, the following changes related to the use of the surgical cutting device are recommended: changes to the ergonomic positioning of the surgical cutting device, changes to the technology, manual changes to performance-affecting components (such as damping components) (e.g., the positioning, characteristics, etc. of the damping component or other performance-affecting components); or changes to a different surgical cutting device or a portion thereof.

[0020] In another aspect of this disclosure, the sensor data includes at least one of the following: vibration data, positioning data, acceleration data, optical data, audio data, force data, temperature data, and / or motor electrical characteristic data. Attached Figure Description

[0021] The above and other aspects and features of this disclosure will become more apparent when considered in conjunction with the accompanying drawings, in which the same reference numerals identify similar or identical elements.

[0022] Figure 1 This is a perspective view of a surgical system according to the present disclosure, which includes a console and a powered surgical cutting device;

[0023] Figure 2 Examples are provided for configuration with Figure 1 Various different rotary cutting ends are used in the powered surgical cutting device;

[0024] Figures 3A to 3C It is configured to be used with Figure 1 A perspective view of various surgical saw-powered surgical cutting devices used in surgical systems;

[0025] Figure 4 Based on this disclosure Figure 1 A side view of a powered surgical cutting device, which includes multiple sensors positioned at various locations.

[0026] Figure 5 Based on this disclosure Figure 1 A longitudinal sectional view of a powered surgical cutting device, which includes multiple sensors positioned at various locations.

[0027] Figure 6 yes Figure 1 A block diagram of the controller for the console;

[0028] Figure 7 It is a logic diagram of the algorithm according to this disclosure;

[0029] Figure 8 It is a logic diagram of the machine learning algorithm based on this disclosure;

[0030] Figure 9 This is a flowchart of the method according to this disclosure;

[0031] Figure 10A and Figure 10B They are Figure 1 The distal portion of the powered surgical cutting device is shown in a side partial sectional view during use, with initial and adjusted configurations for cutting tissue; and

[0032] Figure 11A and Figure 11B yes Figure 1 The front view of the console displays both the initial settings and the adjusted settings. Detailed Implementation

[0033] Go to Figure 1The surgical system 10 provided according to this disclosure includes a console 100 and one or more surgical cutting devices 300. The console 100 may include an outer housing 110 enclosing the internal operable components of the console 100, a touchscreen graphical user interface (GUI) 120 for receiving user input and displaying information to the user, multiple device ports 130, one or more fluid pumps 140, and / or other suitable features. One or more controllers 600 (see [link to relevant documentation]) include one or more processors and associated memory. Figure 6 The controller 600 is housed within the outer casing 110 and serves the following functions: providing power and control signals to devices connected to the console 100; processing user input, feedback data, and other data received at the console 100; and controlling one or more fluid pumps 140. (See controller 600 for more details.) Figure 6 A portion of or other suitable hardware and drive mechanisms, excluding the controller, may be housed within the outer housing 110 to perform various functions of the console 100, and may include, for example, one or more central processing units (CPUs) and / or microcontroller units (MCUs), power generation and control hardware and corresponding firmware / software stored on the power generation and control hardware, sensor circuits, motors, pump drivers, pump controllers, etc.

[0034] One or more surgical cutting devices 300 may be defined in any suitable configuration for performing various surgical tasks, for various procedures, etc. An example of a suitable surgical cutting device (surgical cutting device 300) typically includes a handle 310, a shaft assembly 320 extending distally from the handle 310 (releasably or integrally connected thereto), a cutting tool 330 extending distally from the shaft assembly 320, 310 (releasably or integrally connected thereto), a motor 340 disposed within the handle 310 and operatively coupled to the cutting tool 330 to drive rotation and / or reciprocating motion of the cutting tool 330 relative to the shaft assembly 320 to cut tissue, and a cable 350 connecting the motor 340 to a console 100 such that the console 100 can power the motor 340 and control the motor, thereby controlling the cutting tool 330. In various aspects, the shaft assembly 320 includes a rotating collar 322 rotatable relative to the shank 310 to advance or retract relative to the cutting tool 330 (depending on the direction of rotation of the rotating collar 322) the outer sleeve 324 of the shaft assembly 320 to expose more or less of the cutting tool 330 at the distal end of the outer sleeve 324. The motor 340 may be an electric motor, a pneumatic motor, an ultrasonic transducer, or other suitable motor configured to drive the cutting tool 330 to rotate and / or reciprocate to cut tissue. The console 100 is configured to drive and control the motor 340, such as the speed, torque, etc., output by the motor 340. In various aspects, the surgical cutting device 300 may include additional features such as, for example, manual control, navigation, articulation, etc.

[0035] The cutting tool 330 can be defined in any suitable configuration and can be integrated with or removed from the surgical cutting device 300. More specifically, and further refer to... Figure 2 Various rotary cutting tools 332 can be configured for releasable attachment to the surgical cutting apparatus 300. In various aspects, the rotary cutting tool 332 can be releasably engaged with a shaft assembly 320 (which can then be releasably or integrally connected to the shank 310). Alternatively, the rotary cutting tool 332 can be integrally integrated with a corresponding shaft assembly 320, which can then be releasably engaged with the shank 310. In either configuration, the surgical cutting apparatus 300 can therefore be interchangeably customized with a particular rotary cutting tool 332, depending on the specific purpose. Reciprocating cutting tools and / or cutting tools configured for both rotary and reciprocating motions are also contemplated.

[0036] refer to Figures 3A to 3C In addition to the rotary cutting tool 332 ( Figure 2In addition to or as an alternative to these, the shank 310 may be releasably or integrally connected to shaft assemblies 322a, 322b, 322c, which include corresponding sawing tools 334a, 334b, 334c, configured for longitudinal reciprocating motion along the longitudinal axis of shaft assembly 322a, oscillating motion about an axis substantially parallel to the longitudinal axis of shaft assembly 322b, or oscillating motion about an axis substantially perpendicular to the longitudinal axis of shaft assembly 322c, respectively. Other suitable sawing tools are also contemplated.

[0037] refer to Figure 4 and Figure 5 The surgical cutting device 300 is shown. Figure 1 The shaft assembly 320 includes a cutting tool 330 extending distally from the surgical cutting device. Although the shaft assembly 320 and the cutting tool 330 have been described in detail, the aspects and features of this disclosure described in detail below are equally applicable to use with other shaft assemblies and cutting tools or any other suitable shaft assembly and / or cutting tool described in detail herein.

[0038] As noted above, the shaft assembly 320 includes a rotating collar 322 and an outer sleeve 324, and also includes a proximal hub 326 and a plurality of bearings 328, the proximal hub being configured to releasably (or otherwise integrally) connect the shaft assembly 320 to the shank 310. Figure 1 The plurality of bearings are configured to movably support the cutting tool 330 within the outer sleeve 324, thereby allowing the cutting tool 330 to rotate and / or translate relative to the outer sleeve 324 to cut tissue. The rotating collar 322 connects the outer sleeve 324 to the proximal hub 326 (and thus the shank 310) via a lead screw coupling 323. Figure 1 The outer sleeve 324 is operably engaged such that, as noted above, rotation of the rotating collar 322 causes the outer sleeve 324 to advance or retract around and relative to the cutting tool 330. Although this adjustment (e.g., advance and retraction) of the outer sleeve 324 relative to the cutting tool 330 is shown and described as manual, it is also conceivable that it can be adjusted using a motor 340. Figure 1 Alternatively, a separate motor can be used to provide power to the outer sleeve 324 relative to the cutting tool 330 (and in all respects, automatically) adjust, for example, advance and retract.

[0039] The cutting tool 330 extends through the outer sleeve 324 and can be configured to work with the motor 340. Figure 1The cutting tool 330 can be directly or indirectly connected to achieve rotary drive, reciprocating drive, and / or other kinematic drive. The cutting tool 330 also includes a distal working end 334 extending distally from the outer sleeve 324. The distal working end 334 can define any suitable configuration, such as, but not limited to, [missing information]. Figure 2 The configurations shown are examples.

[0040] Continue to refer to Figure 4 and Figure 5 And refer to other sources. Figure 1 The surgical cutting device 300 may include one or more sensors 350, which are disposed at various locations on or within one or more components or assemblies of the surgical cutting device 300. One or more sensors 350 may include: vibration or inertial sensors, such as piezoelectric sensors, accelerometers, gyroscopes, magnetometers, or combinations thereof (e.g., to monitor vibration / motion of the cutting tool 330 and / or the outer sleeve 324); positioning or displacement sensors, such as optical and / or laser sensors for obtaining displacement, positioning, and / or vibration data; force sensors (e.g., for monitoring force, torque, and / or strain on the cutting tool 330 and / or the outer sleeve 324); audio sensors (e.g., for monitoring noise generated by the surgical cutting device 300 and / or its components at the interface between the cutting tool 330 and tissue); electrical characteristic sensors (e.g., sensors configured to monitor current (such as motor current), impedance, voltage, power, and their probability); and / or temperature sensors (e.g., for monitoring temperature of the surgical cutting device 300 and / or its components at the interface between the cutting tool 330 and tissue). Other suitable sensors are also contemplated. In various respects, a single sensor 350 is provided. In other respects, multiple sensors 350 of the same type are disposed at various locations on or within the surgical cutting device 300. In yet another respect, one or more sensors 350 of the first type and one or more sensors 350 of a different second type are disposed at the same and / or different locations on or within the surgical cutting device 300.

[0041] Regarding the location of sensor 350 on or within surgical cutting device 300, sensor 350 may, for example, and as... Figure 4 and Figure 5The following configurations are shown: on or inside the rotating collar 322; on or inside the outer sleeve 324 (towards the proximal end, distal end, and / or intermediate position of the outer sleeve 324); between the outer sleeve 324 and the cutting tool 330; on or inside the proximal hub 326; connected to or coupled to the bearing 328; on or inside the cutting tool 330 (inside the outer sleeve 324 and / or on or inside the exposed portion of the cutting tool 330; towards the proximal end, distal end, and / or intermediate position of the cutting tool 330); in the motor 340 ( Figure 1 The drive rotor 342 is located on or inside the drive rotor, which is driven by the motor 340. Figure 1 ) drives and subsequently drives the movement of the cutting tool 330; and / or with the motor 340 ( Figure 1 ) and / or associated with the electrical input to the motor (whether set in motor 340 ( Figure 1 On or inside the motor, such as, for example, on console 100 ( Figure 1 (within). The sensor 350 may be located at any other suitable location. Specifically, the sensor 350 may be located at a location where the characteristics to be sensed undergo detectable changes according to the performance conditions of the surgical cutting apparatus 300. For example, a temperature sensor, a vibration sensor, and / or a force sensor may be located at a corresponding location where the surgical cutting apparatus 300 tends to heat up, vibrate more, and / or experience increased forces when it is operating under unstable conditions compared to normal conditions.

[0042] Suitable wires, conductive structures, electrical traces, contacts, wireless connection interfaces, combinations thereof (not explicitly shown) are provided on or within the surgical cutting device 300 (and / or its components) to electrically connect one or more sensors 350 to the console 100.

[0043] Regardless of the specific type and / or location of one or more sensors 350, the one or more sensors 350 are configured to provide data indicative of one or more characteristics of the surgical cutting device 300, which, individually or in combination with feedback from additional sensors 350, other sensors associated with or separate from the surgical cutting device 300, data input by the user, inputs / received from components of the surgical cutting device 300 or other devices, enables the determination of the performance conditions of the surgical cutting device 300. The performance conditions of the surgical cutting device 300 may include, for example, stability and / or efficiency. Regarding stability, sensor data, as well as additional data in various aspects, can be used (and in real-time in various aspects) to determine the stability of the surgical cutting device 300 during use. Stability may be a binary output, for example, whether the surgical cutting device 300 is operating in a stable or unstable manner. Alternatively, stability may be provided as a stability level, for example, on a numerical scale (e.g., stability on a scale of 1 to 10 or 1 to 100) or on a symbolic scale (e.g., stability is indicated as green, yellow, or red). Sensor data that can be used to determine the stability of the surgical cutting device 300, which indicates the stability performance conditions, includes, for example, but not limited to: vibration or motion data; force, torque and / or strain data; audio data; and / or temperature data.

[0044] Regarding efficiency, sensor data, as well as additional data in various aspects, can be used (and in real time in various aspects) to determine the efficiency of the surgical cutting device 300 during use. Efficiency can be a binary output, for example, whether the surgical cutting device 300 is operating in an efficient or inefficient manner. Alternatively, stability can be provided as an efficiency level, for example, on a digital scale (e.g., efficiency on a scale of 1 to 10 or 1 to 100) or on a symbolic scale (e.g., efficiency is indicated by green, yellow, or red). Sensor data indicating the efficiency of the surgical cutting device 300 that can be used to determine efficiency performance conditions include, for example, but not limited to: vibration or motion data; force, torque, and / or strain data; and / or electrical characteristics.

[0045] Other sensors associated with or separate from the surgical cutting apparatus 300 that provide data suitable for determining the performance conditions of the surgical cutting apparatus 300 include, for example, but not limited to: image sensors for real-time imaging of a field of view including at least the cutting tool 330 and / or tissue cut by the cutting tool 330 (e.g., video imaging, thermal imaging, ultrasound imaging, etc.); impedance and / or other electrical characteristic sensors, for example, for measuring the tissue conductivity (and / or other electrical characteristics) of the cut tissue; force / pressure sensors, for example, for measuring the force or pressure applied to the cut tissue; and / or other suitable sensors. Such sensors enable, for example, the determination of the characteristics of the cut tissue and / or the determination of the type of tissue cut. Determining the characteristics of the cut tissue includes tissue type (soft or hard tissue), tissue thickness, tissue density, tissue condition (healthy or diseased), transitions between tissues (e.g., transitions between tissue layers, tissue types, etc., entry into or exit from anatomical cavities), etc. Determining the type of tissue to be cut includes determining whether the tissue is, for example, bone, cartilage, muscle, organ, etc.

[0046] See still Figure 1 , Figure 4 and Figure 5 Data regarding the characteristics and / or type of tissue being cut can be used in conjunction with data from one or more sensors 350 to determine the performance conditions of the surgical cutting device 300 during use. More specifically, because the surgical cutting device 300 can exhibit different characteristics when cutting tissues with different properties and / or different types of tissue (e.g., where the surgical cutting device 300 generates more heat and vibration when cutting bone or harder tissue compared to cutting cartilage or softer tissue, or where a spike in motor current occurs in response to a transition from cutting soft tissue to cutting hard tissue), data regarding the characteristics and / or type of tissue being cut can be used to contextualize the data provided by the sensors 350. For example, temperature, vibration amplitude, and / or motor current, or changes thereof, may be typical for cutting one type of tissue or tissue with certain characteristics; however, the same temperature, vibration amplitude, and / or motor current, or changes thereof, may indicate instability and / or inefficiency when exhibiting instability and / or inefficiency during cutting another type of tissue or tissue with other characteristics.

[0047] Other data that may be used to facilitate the determination of the performance conditions of the surgical cutting device 300 during use may include data input by the user, input read / received from components or the device, and / or other data. This data may include data relating to the surgical cutting device 300 and / or its components (e.g., attached shaft assembly 320 and / or cutting tool 330), including, but not limited to: device / component ID; device / component type; device / component batch number; device / component manufacturing date; surgeon and / or hospital data; patient data; procedure data; etc. Because the surgical cutting device 300 may exhibit different characteristics when cutting tissue depending on the type of surgical cutting device 300 (and / or its components), age and / or configuration, the technology used, the method employed, the surgeon's experience, the type of procedure being performed, and / or the patient's condition and / or anatomy, such data can be used to contextualize the data provided by the sensor 350.

[0048] For example, the forces, strains, and / or torques or variations thereof encountered during the use of the surgical cutting apparatus 300 may be typical for one procedure or technique; however, the same forces, strains, and / or torques or variations thereof may indicate instability and / or inefficiency when exhibiting instability and / or inefficiency during tissue cutting in another procedure or using another technique. As another example, temperature, vibration amplitude, and / or motor current or variations thereof may be typical when using a cutting tool 330, shaft assembly 320, and / or shank 310 of one type and / or age; however, the same temperature, vibration amplitude, and / or motor current or variations thereof may indicate instability and / or inefficiency exhibited when using a cutting tool 330, shaft assembly 320, and / or shank 310 of another type and / or age.

[0049] In various respects, for the purpose of reading / writing at least some of the other data mentioned above, some or all components of the surgical cutting device 300 (e.g., handle 310, shaft assembly 320, and / or cutting tool 330) include RFID or other suitable communication chips (not explicitly shown) with memory for storing data. For example, handle 310, shaft assembly 320, and / or cutting tool 330 may include memory (e.g., read-only memory) that stores identification data (e.g., unique ID, device / part type, batch number, manufacturing date, configuration data, features, parts, and / or settings) that can be read by console 100. Handle 310, shaft assembly 320, and / or cutting tool 330 may additionally or alternatively include memory (e.g., read / write memory) that can be read and / or written by console 100 to store, for example, usage counts, disinfection counts, usage data, event / error logs, usage and / or operation flags, etc. Data sent to / from the surgical cutting device 300 (and / or its components) may be transmitted via wired or wireless networks or any other suitable means to be stored on a remote server (including a cloud server), thereby enabling the management and tracking of such information. Furthermore, in addition to onboard memory, the surgical cutting device 300 (and / or its components) may include barcodes or other identifiers so that data from such barcodes or other identifiers can be associated with the surgical cutting device 300 (and / or its components), thereby enabling management and tracking at a remote server. Additionally, supplementary data may include data from robotic surgical systems, navigation systems, and / or other systems associated with the use of the surgical cutting device 300.

[0050] Go to Figure 6 The console 100 is described in detail. Figure 1 The controller 600. Although the controller 600 is described in detail as console 100 ( Figure 1 It is part of the surgical cutting device 300, but the controller 600 may optionally be integrated into the surgical cutting device 300. Figure 1In this system, the controller 600 is distributed across console 100 and surgical cutting device 300, or across multiple devices including cloud servers and / or remote devices connected via a network or other communication links. Controller 600 includes a processor 610 connected to a computer-readable storage medium or memory 620, which may be volatile type memory (e.g., RAM) or non-volatile type memory (e.g., flash memory, disk drive, etc.). In various aspects, processor 610 may be, but is not limited to, a digital signal processor, microprocessor, ASIC, graphics processing unit (GPU), field-programmable gate array (FPGA), or central processing unit (CPU). In various aspects, memory 620 may be random access memory, read-only memory, disk drive, solid-state memory, optical disc drive, and / or another type of memory. In various aspects, memory 620 may be separable from controller 600 and may communicate with processor 610 via a communication bus on a circuit board and / or via a communication cable such as a serial ATA cable or other type of cable. Memory 620 includes computer-readable instructions executable by processor 610 to operate controller 600. In various aspects, controller 600 includes a network interface 630 for communicating with other computers or servers. In various aspects, storage device 640 can be used to store data. In various embodiments, controller 600 may include one or more FPGAs 650. FPGA 650 can be used to perform computations and / or execute algorithms including machine learning algorithms.

[0051] Memory 620 stores appropriate instructions to be executed by processor 610 for receiving sensed data, such as from sensor 350. Figure 4 and Figure 5 The sensed data, and any other data; access the storage device 640 of the controller 600; determine the surgical cutting device 300 ( Figure 1 The performance conditions; and based on the determined performance conditions, adjusting the operating settings (thus providing automatic adaptive control) and / or recommending changes (thus enabling manual adaptive control).

[0052] Determine the surgical cutting device 300 ( Figure 1 The performance requirements may initially include processing the received data, such as from sensor 350 ( Figure 4 and Figure 5 The data processing may include, for example, evaluating sensor data over time, calculating statistics (average, maximum, minimum, etc.), determining the rate of change (direction and magnitude), identifying steady-state conditions and deviations from steady-state conditions, etc.

[0053] For further reference Figure 7Sensed data 710 (in aspects where no initial processing is performed, whether processed or raw data) along with other data 720 is input into one or more algorithms 730 (e.g., including one or more thresholds stored in one or more lookup tables in storage device 640) to determine performance conditions 740. Algorithms 730, and more specifically, their applicable thresholds, may vary based on time data, different processed data from the same sensor 350, data from different sensors 350, and / or other data 720. For example, unfavorable performance conditions (e.g., instability and / or inefficiency) may be determined if the sensed data exceeds a first threshold for a first time period, or if the sensed data does not exceed the first threshold but exceeds a second lower threshold for a second longer time period. As another example, unfavorable performance conditions (e.g., instability and / or inefficiency) may be determined if the first sensed data exceeds a first threshold regardless of other sensed data, or if the first sensed data does not exceed the first threshold but exceeds a second lower threshold and the second sensed data also exceeds the threshold. As yet another example, the threshold does not need to be universal, but can be adjusted based on other data obtained, such as data that can help put the sensor data into context, as detailed above.

[0054] As noted above, the determination of performance condition 740 (e.g., stability and / or efficiency) can be a binary output or a scaled (digital or symbolic) output. In configurations providing scaled output, different thresholds can be used to determine performance condition 740 on the corresponding scale. Regardless of the form of determination, once determined, controller 600 provides instructions and / or outputs based on the determined performance condition 740, as detailed below.

[0055] refer to Figure 6 and Figure 8 In various aspects, the controller 600 utilizes one or more machine learning algorithms 810 to determine performance conditions. The machine learning algorithms 810 may utilize base data 820 (e.g., experimental data and / or data from previous procedures initially input into one or more machine learning algorithms 810); sensed data 830, for example, from sensor 350 (…). Figure 4 and Figure 5 The machine learning algorithm 810 is trained and learns from the sensed data (and / or other data 840) so that it can determine performance conditions 850. In various respects, the machine learning algorithm 810 can be trained by the console 100 ( Figure 1The algorithm can be executed by an external computing device and the resulting algorithm can be transmitted to the controller 600. Furthermore, training can be performed initially and the machine learning algorithm 810 can be locked thereafter, or the machine learning algorithm 810 can be trained and updated continuously or discretely based on data acquired during use, such as updates according to a schedule.

[0056] As noted above, the determination of performance condition 850 (e.g., stability and / or efficiency) can be a binary output or a scaled (digital or symbolic) output. The output (e.g., binary or scaled) may indicate the type of machine learning algorithm 810 utilized. For example, classification machine learning techniques may be utilized, in which a relatively small selection of binary or scaled outputs is used. On the other hand, regression machine learning techniques may be utilized, in which a relatively large selection of scaled outputs (e.g., 1 to 100) is used. One or more machine learning algorithms 810 may implement one or more of the following: supervised learning, semi-supervised learning, unsupervised learning, reinforcement learning, association rule learning, decision tree learning, anomaly detection, feature learning, computer vision, etc., and may be modeled as one or more of neural networks, Bayesian networks, support vector machines, genetic algorithms, etc. Once determined, controller 600 provides instructions and / or outputs based on the determined performance condition 850, as detailed below.

[0057] Go to Figure 9 The method 900 according to this disclosure is shown. As noted above, during use, sensor feedback and / or other data are received, as indicated at 910. Based on the sensor feedback and / or other data, as indicated at 920, one or more performance conditions are determined. The determination of one or more performance conditions may be made continuously, periodically, or in any other suitable manner. A binary output regarding the determination of one or more performance conditions, for example, if an unfavorable performance condition (e.g., instability and / or inefficiency) is determined, the method proceeds to 930 and / or 940. At 930, a recommended change is output, for example, controller 600 ( Figure 6 ) provides instructions for, for example, visual output (e.g., console 100 (see) Figure 1 The GUI 120 contains graphics and / or text) and / or audible output (e.g., from the console 100). Figure 1 The recommended changes are output in the form of an associated speaker. These recommended changes can guide the user to take one or more corrective actions to remedy adverse performance conditions (e.g., instability and / or inefficiency). Recommended corrective actions may include, for example, changes to the technology, alterations to the ergonomic positioning for better balance and / or support of the surgical cutting device 300. Figure 1Using lower speeds, reducing pressure / force, and in surgical cutting devices 300 ( Figure 1 Blockage and reduction of cutting tools 330 ( Figure 1 For example, by rotating the rotating collar 322 to advance or retract the outer sleeve 324 of the shaft assembly 320 relative to the cutting tool 330, changing the tool type and / or size, etc. Regarding the scaled output, the recommended number and / or type of correction actions may vary depending on the scaled output.

[0058] At 940, alternatively or additionally, if adverse performance conditions (e.g., instability and / or low efficiency) are determined to exist, then controller 600 ( Figure 6 Provides instructions to automatically adjust the console 100 and / or surgical cutting device 300 based on identified adverse performance conditions (see...). Figure 1 The settings for controller 600 (for example). Figure 6 ) can provide commands to control the surgical cutting device 300 (see Figure 1 The motor 340 automatically reduces motor speed, reduces motor torque, and advances or retracts the outer sleeve 324 of the shaft assembly 320 relative to the cutting tool 330 (in which such adjustments are automatic). Regarding the scaled output, the severity and / or type of corrective actions taken may vary depending on the scaled output.

[0059] In various respects, in response to the detection of adverse performance conditions (or adverse performance conditions exceeding a threshold), automatic adjustments may include safety shut-off prevention operations or safety pause prevention operations for a predetermined amount of time and / or until the adverse performance conditions cease. In robot implementations, this may additionally or alternatively include removing the instrument from or moving it to a safe location within the surgical site.

[0060] Furthermore, in cases where adverse performance conditions are (e.g., as sensed by a temperature sensor or thermal camera) overheating or thermal conditions, automatic adjustments may include increasing the flushing flow (in this case, it is provided for use with the surgical cutting device 300). Figure 1 (To be used together) to increase the surgical cutting device 300 ( Figure 1 ( ) cooling and recovery from adverse performance conditions.

[0061] After recommending changes at 930 and / or adjusting settings at 940, or if it is determined that no adverse performance conditions exist (i.e., if normal performance conditions are detected), the method returns to 910 to evaluate the new data and, as detailed above, again determines whether adverse performance conditions exist and, if so, what action to take in response.

[0062] refer to Figure 10A and Figure 10B This illustrates the distal portion of a surgical cutting device 300 for cutting tissue “T” in use, wherein the outer sleeve 324 of the shaft assembly 320 is positioned in a retracted position and an extended position relative to the cutting tool 330, respectively, to expose more or less of the cutting tool 330 at the distal end of the outer sleeve 324. In the retracted position (… Figure 10A In (where more of the cutting tool 330 is exposed at the distal end of the outer sleeve 324), the cutting tool 330 is less constrained, and therefore its movement is less damped and / or relatively less rigid. This allows for improved cutting performance during use under normal performance conditions. However, in this retracted positioning ( Figure 10A In this context, when operating under adverse performance conditions, the surgical cutting device 300 may be more prone to instability and / or inefficiency. Therefore, depending on the determined performance conditions, the outer sleeve 324 may be automatically moved, or a suggestion may be provided to move the outer sleeve 324 from its retracted position. Figure 10A Move to extended positioning ( Figure 10B In extended positioning () Figure 10B In this configuration, less of the cutting tool 330 is exposed at the distal end of the outer sleeve 324, resulting in greater constraint on the cutting tool 330 and thus damping of its movement and reduced vibration. Additionally or alternatively, the stiffness of the cutting tool 330 is increased, further constraining its movement. This leads to improved stability and / or efficiency. In configurations where performance conditions are determined according to a scaling factor, the extended positioning (e.g., the degree to which the outer sleeve 324 moves distally around the cutting tool 330) can be determined based on scaled performance conditions, such as when the outer sleeve 324 is further advanced distally around the cutting tool 330 when a more severe instability is detected compared to a less severe instability. Regardless of the specific implementation, this disclosure enables real-time tuning (or a preferred method thereof) of the surgical cutting apparatus 300 based on system feedback, which in some cases may deviate from the operator's orientation and / or common perception, thereby providing adaptive control that is superior to and exceeds what can be provided manually.

[0063] refer to Figure 11A and Figure 11B The diagram shows a console 100, where a GUI 120 is displaying initial operating settings for speed (RPM) 1110 and torque (a predetermined percentage of a torque reference value) 1120 during use, as well as adjusted operating settings for speed 1110 and torque 1120 during use. Based on the determined performance conditions, the controller 600 ( Figure 6 ) Automatically adjust motor 340 ( Figure 1The speed 1110 and / or torque 1120 are set to improve stability and / or efficiency, and to enable safe continued use in response to the detection of adverse performance conditions. More specifically, reducing the speed and / or torque can reduce vibration, temperature hotspots, excessive forces, etc., thereby improving stability and / or efficiency. The amount of speed and / or torque adjustment (e.g., reduction) may depend on, for example, the detected level of instability and / or inefficiency (e.g., in the case of determined scaled performance conditions).

[0064] While several aspects of this disclosure have been shown in the accompanying drawings, it is not intended to limit this disclosure, as it is intended to be as broad as permitted by the art to which it belongs and to be read in the same manner. Therefore, the above description should not be construed as restrictive, but merely as illustrative of particular aspects. Those skilled in the art will be able to conceive of other modifications within the scope and spirit of the appended claims.

Claims

1. A surgical system with adaptive control, the surgical system comprising: a surgical cutting device including a cutting tool and a motor configured to drive movement of the cutting tool; at least one sensor configured to generate sensor data indicative of at least one characteristic of the surgical cutting device during use; and a controller configured to receive the sensor data and determine a performance condition of the surgical cutting device based at least on the sensor data, the controller being further configured to, when the determined performance condition is an adverse performance condition, at least one of adjust a setting of the surgical cutting device or recommend a change related to use of the surgical cutting device.

2. The surgical system of claim 1, wherein the controller is further configured to receive other data and determine a performance condition based at least on the sensor data and the other data.

3. The surgical system of claim 2, wherein the other data includes at least one of identification data, patient data, procedure data, robotic system data, or navigation data.

4. The surgical system of claim 1, wherein the determined performance condition includes at least one of a stability condition or an efficiency condition.

5. The surgical system of claim 1, wherein the determined performance condition is a binary determination.

6. The surgical system of claim 1, wherein the determined performance condition is a scaled determination.

7. The surgical system of claim 1, wherein the controller is configured to, when the determined performance condition is an adverse performance condition, adjust a setting of the surgical cutting device by adjusting at least one of a speed of the motor, a torque of the motor, or a performance- affecting component of the surgical cutting device.

8. The surgical system of claim 1, wherein the controller is configured to, when the determined performance condition is an adverse performance condition, recommend a change related to use of the surgical cutting device by recommending a manual change to a performance-affecting component of the surgical cutting device.

9. The surgical system of claim 1, wherein the at least one sensor includes at least one of a vibration sensor, an audio sensor, a force sensor, a torque sensor, a temperature sensor, an optical sensor, or a motor electrical property sensor.

10. The surgical system of claim 1, wherein the surgical cutting device further includes a handle that houses the motor therein and a shaft assembly coupled to the handle and including an outer sleeve, wherein the cutting tool extends through the outer sleeve of the shaft assembly.

11. The surgical system of claim 10, wherein the at least one sensor is disposed on or within at least one of the handle, the outer sleeve, or the cutting tool.

12. The surgical system of claim 1, wherein the controller is configured to determine the performance condition in real-time and, when the determined performance condition is an adverse performance condition, at least one of adjust the setting of the surgical cutting device or recommend the change related to use of the surgical cutting device.

13. The surgical system of claim 1, further comprising a console configured to supply power and control signals to the surgical cutting device, wherein the controller is disposed within the console.

14. The surgical system of claim 1, wherein the controller is configured to implement at least one machine learning algorithm to determine the performance condition.

15. A method of adaptive control of a surgical system, the method comprising: driving a motor to move a cutting tool of a surgical cutting device to cut tissue; monitoring sensor data indicative of at least one characteristic of the surgical cutting device during the cutting of the tissue; determining a performance condition of the surgical cutting device based at least on the sensor data; and when the determined performance condition is an adverse performance condition, at least one of adjusting a setting of the surgical cutting device or recommending a change related to use of the surgical cutting device.

16. The method of claim 15, further comprising: receiving other data comprising at least one of identification data, patient data, or procedure data, wherein the performance condition is determined based at least on the sensor data and the other data.

17. The method of claim 15, wherein the determined performance condition comprises at least one of a stability condition or an efficiency condition. adjusting the setting of the surgical cutting device by adjusting at least one of a speed of the motor, a torque of the motor, or a performance-impacting component of the surgical cutting device when the determined performance condition is an adverse performance condition.

18. The method of claim 15, wherein, recommending a change related to use of the surgical cutting device by recommending a manual change of a performance-impacting component of the surgical cutting device when the determined performance condition is an adverse performance condition.

19. The method of claim 15, wherein, 20. The method of claim 15, wherein the sensor data comprises at least one of vibration data, audio data, torque data, optical data, force data, temperature data, or motor electrical property data. ​

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