EP4712896A1 - Systems and methods for preventing and detecting skiving - Google Patents

Abstract

Systems and methods for planning a cutting process to prevent skiving and for preventing skiving are provided. A three-dimensional model of a target anatomical element may be received. One or more inputs of the cutting process including a cutting plane may also be received. One or more parameters of the cutting process may be determined based on the cutting plane and the 3D model.

Description

SYSTEMS AND METHODS FOR PREVENTING AND DETECTING SKIVING

CROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Application No. 63/545,895, filed on October 26, 2023 and titled “SYSTEMS AND METHODS FOR PREVENTING AND ETECTING SKIVING”, and U.S. Provisional Application No. 63/466,605, filed on May 15, 2023 and titled “SYSTEMS AND METHODS FOR PREVENTING AND ETECTING SKIVING”, of which each application is incorporated herein by reference in its entirety.

BACKGROUND

[0002] The present disclosure is generally directed to surgical planning, and relates more particularly to planning a cutting process to prevent skiving and detecting and/or mitigating skiving during the cutting process.

[0003] Surgical robots may assist a surgeon or other medical provider in carrying out a surgical procedure, or may complete one or more surgical procedures autonomously. Providing controllable linked articulating members allows a surgical robot to reach areas of a patient anatomy during various medical procedures.

BRIEF SUMMARY

[0004] Example aspects of the present disclosure include:

[0005] A system for planning a cutting process to prevent skiving according to at least one embodiment of the present disclosure comprises a processor; and a memory storing instructions for execution by the processor that, when executed, causes the processor to: receive a three-dimensional (3D) model of a target anatomical element; receive one or more inputs of the cutting process including a cutting plane; and determine one or more parameters of the cutting process based on the cutting plane and the 3D model.

[0006] Any of the aspects herein, wherein the memory stores further instructions for execution by the processor that, when executed, causes the processor to: receive at least one of an approval of the cutting process or an adjustment to the cutting process.

[0007] Any of the aspects herein, wherein determining the one or more parameters of the cutting process includes determining the cutting angle based on a normality to the target anatomical element and a shape of the surgical tool. [0008] Any of the aspects herein, wherein determining the one or more parameters of the cutting process includes determining at least one of a plunge cut or side cut for the surgical tool.

[0009] Any of the aspects herein, wherein the information about the cutting plane on the 3D model is received as input from a user.

[0010] A system for preventing skiving during a cutting process according to at least one embodiment of the present disclosure comprises a robotic arm configured to orient and operate a surgical tool; at least one sensor; a processor; and a memory storing instructions for execution by the processor that, when executed, cause the processor to: cause the robotic arm to operate the surgical tool; receive sensor data from the at least one sensor; and adjust at least one parameter of the surgical tool based on the sensor data.

[0011] Any of the aspects herein, wherein the at least one parameter comprises a cutting pressure, a cutting speed, a cutting oscillation, a cutting angle of the surgical tool, or a robotic arm speed.

[0012] Any of the aspects herein, wherein the at least one parameter comprises the cutting angle and the adjusting the cutting angle comprises determining the cutting angle based on a normality of the surgical tool to a target anatomical element and a shape of the surgical tool.

[0013] Any of the aspects herein, wherein the normality of the surgical tool is determined from pose information of the surgical tool received from the robotic arm. [0014] Any of the aspects herein, wherein the at least one parameter comprises the cutting angle and the adjusting the cutting angle comprises determining at least one of a plunge cut or side cut.

[0015] Any of the aspects herein, wherein the sensor data comprises torque data or force data.

[0016] Any of the aspects herein, wherein the cutting speed and the robotic arm speed are adjusted based on the torque data and the force data.

[0017] Any of the aspects herein, wherein the cutting oscillation and the robotic arm speed are adjusted based on the force data.

[0018] Any of the aspects herein, wherein the memory stores further instructions for execution by the processor that, when executed, causes the processor to: cause the robotic arm to stop operating the surgical tool when the sensor data meets or exceeds a predetermined threshold. [0019] A system for planning a cutting process to prevent skiving according to at least one embodiment of the present disclosure comprises a surgical tool; a robotic arm configured to orient and operate the surgical tool; at least one sensor; a processor; and a memory storing instructions for execution by the processor that, when executed, causes the processor to: receive a three-dimensional (3D) model of a target anatomical element; receive information about a cutting plane on the 3D model; and determine one or more parameters of the cutting process based on the cutting plane and the 3D model.

[0020] Any of the aspects herein, wherein the sensor is positioned on at least one of the robotic arm or the surgical tool.

[0021] Any of the aspects herein, wherein the surgical tool comprises at least one of an ultrasonic cutting or an oscillating cutting tool.

[0022] Any of the aspects herein, wherein the at least one parameter comprises a cutting pressure, a cutting speed, a cutting oscillation, a cutting angle of the surgical tool, or a robotic arm speed.

[0023] Any of the aspects herein, wherein the at least one parameter comprises the cutting angle and the adjusting the cutting angle comprises determining the cutting angle based on a normality of the surgical tool to a target anatomical element and a shape of the surgical tool.

[0024] Any aspect in combination with any one or more other aspects.

[0025] Any one or more of the features disclosed herein.

[0026] Any one or more of the features as substantially disclosed herein.

[0027] Any one or more of the features as substantially disclosed herein in combination with any one or more other features as substantially disclosed herein.

[0028] Any one of the aspects/features/embodiments in combination with any one or more other aspects/features/embodiments.

[0029] Use of any one or more of the aspects or features as disclosed herein.

[0030] It is to be appreciated that any feature described herein can be claimed in combination with any other feature(s) as described herein, regardless of whether the features come from the same described embodiment.

[0031] The details of one or more aspects of the disclosure are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the techniques described in this disclosure will be apparent from the description and drawings, and from the claims. [0032] The phrases “at least one”, “one or more”, and “and/or” are open-ended expressions that are both conjunctive and disjunctive in operation. For example, each of the expressions “at least one of A, B and C”, “at least one of A, B, or C”, “one or more of A, B, and C”, “one or more of A, B, or C” and “A, B, and/or C” means A alone, B alone, C alone, A and B together, A and C together, B and C together, or A, B and C together. When each one of A, B, and C in the above expressions refers to an element, such as X, Y, and Z, or class of elements, such as XI -Xn, Yl-Ym, and Zl-Zo, the phrase is intended to refer to a single element selected from X, Y, and Z, a combination of elements selected from the same class (e.g., XI and X2) as well as a combination of elements selected from two or more classes (e.g., Y1 and Zo).

[0033] The term “a” or “an” entity refers to one or more of that entity. As such, the terms “a” (or “an”), “one or more” and “at least one” can be used interchangeably herein. It is also to be noted that the terms “comprising”, “including”, and “having” can be used interchangeably.

[0034] The preceding is a simplified summary of the disclosure to provide an understanding of some aspects of the disclosure. This summary is neither an extensive nor exhaustive overview of the disclosure and its various aspects, embodiments, and configurations. It is intended neither to identify key or critical elements of the disclosure nor to delineate the scope of the disclosure but to present selected concepts of the disclosure in a simplified form as an introduction to the more detailed description presented below. As will be appreciated, other aspects, embodiments, and configurations of the disclosure are possible utilizing, alone or in combination, one or more of the features set forth above or described in detail below.

[0035] Numerous additional features and advantages of the present disclosure will become apparent to those skilled in the art upon consideration of the embodiment descriptions provided hereinbelow.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS [0036] The accompanying drawings are incorporated into and form a part of the specification to illustrate several examples of the present disclosure. These drawings, together with the description, explain the principles of the disclosure. The drawings simply illustrate preferred and alternative examples of how the disclosure can be made and used and are not to be construed as limiting the disclosure to only the illustrated and described examples. Further features and advantages will become apparent from the following, more detailed, description of the various aspects, embodiments, and configurations of the disclosure, as illustrated by the drawings referenced below.

[0037] Fig. l is a block diagram of a system according to at least one embodiment of the present disclosure;

[0038] Fig. 2A is a cross-sectional view of a three-dimensional (3D) model of an anatomical element and a cutting plane according to at least one embodiment of the present disclosure;

[0039] Fig. 2B is a cross-sectional view of the 3D model and a cutting plane according to at least one embodiment of the present disclosure;

[0040] Fig. 3 A is a schematic drawing of a surgical tool at a cutting angle according to at least one embodiment of the present disclosure;

[0041] Fig. 3B is a schematic drawing of a surgical tool at a cutting angle according to at least one embodiment of the present disclosure;

[0042] Fig. 4A is a cross-sectional view of a 3D model of the anatomical element and a surgical tool according to at least one embodiment of the present disclosure;

[0043] Fig. 4B is a cross-sectional view of a 3D model of the anatomical element and a surgical tool according to at least one embodiment of the present disclosure;

[0044] Fig. 5 is a flowchart according to at least one embodiment of the present disclosure;

[0045] Fig. 6 is a flowchart according to at least one embodiment of the present disclosure;

[0046] Fig. 7 is a flowchart according to at least one embodiment of the present disclosure;

[0047] Fig. 8A is an axial view of an anatomical element and a surgical tool according to at least one embodiment of the present disclosure;

[0048] Fig. 8B is an axial section view of an anatomical element and a surgical tool according to at least one embodiment of the present disclosure;

[0049] Fig. 9A is a lateral view of an anatomical element and a surgical tool according to at least one embodiment of the present disclosure;

[0050] Fig. 9B is a lateral section view of an anatomical element and a surgical tool according to at least one embodiment of the present disclosure;

[0051] Fig. 10A is an axial section view of an anatomical element and a surgical tool according to at least one embodiment of the present disclosure; [0052] Fig. 10B is an isometric view of an anatomical element and a surgical tool according to at least one embodiment of the present disclosure;

[0053] Fig. 11 is an image of an anatomical element according to at least one embodiment of the present disclosure;

[0054] Fig. 12 is an image of multiple cutting paths for a surgical tool according to at least one embodiment of the present disclosure;

[0055] Fig. 13 A is a schematic view of an initial cutting path for a surgical tool according to at least one embodiment of the present disclosure;

[0056] Fig. 13B is a schematic view of a modified cutting path for a surgical tool according to at least one embodiment of the present disclosure;

[0057] Fig. 13C is a schematic view of a surgical tool at different example cutting angles according to at least one embodiment of the present disclosure.

DETAILED DESCRIPTION

[0058] It should be understood that various aspects disclosed herein may be combined in different combinations than the combinations specifically presented in the description and accompanying drawings. It should also be understood that, depending on the example or embodiment, certain acts or events of any of the processes or methods described herein may be performed in a different sequence, and/or may be added, merged, or left out altogether (e.g., all described acts or events may not be necessary to carry out the disclosed techniques according to different embodiments of the present disclosure). In addition, while certain aspects of this disclosure are described as being performed by a single module or unit for purposes of clarity, it should be understood that the techniques of this disclosure may be performed by a combination of units or modules associated with, for example, a computing device and/or a medical device.

[0059] In one or more examples, the described methods, processes, and techniques may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored as one or more instructions or code on a computer-readable medium and executed by a hardware-based processing unit. Alternatively or additionally, functions may be implemented using machine learning models, neural networks, artificial neural networks, or combinations thereof (alone or in combination with instructions). Computer-readable media may include non-transitory computer-readable media, which corresponds to a tangible medium such as data storage media (e.g., RAM, ROM, EEPROM, flash memory, or any other medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer).

[0060] Instructions may be executed by one or more processors, such as one or more digital signal processors (DSPs), general purpose microprocessors (e.g., Intel Core i3, i5, i7, or i9 processors; Intel Celeron processors; Intel Xeon processors; Intel Pentium processors; AMD Ryzen processors; AMD Athlon processors; AMD Phenom processors; Apple A10 or 10X Fusion processors; Apple Al l, A12, A12X, A12Z, or A13 Bionic processors; or any other general purpose microprocessors), graphics processing units (e.g., Nvidia GeForce RTX 2000-series processors, Nvidia GeForce RTX 3000-series processors, AMD Radeon RX 5000-series processors, AMD Radeon RX 6000-series processors, or any other graphics processing units), application specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuitry. Accordingly, the term “processor” as used herein may refer to any of the foregoing structure or any other physical structure suitable for implementation of the described techniques. Also, the techniques could be fully implemented in one or more circuits or logic elements.

[0061] Before any embodiments of the disclosure are explained in detail, it is to be understood that the disclosure is not limited in its application to the details of construction and the arrangement of components set forth in the following description or illustrated in the drawings. The disclosure is capable of other embodiments and of being practiced or of being carried out in various ways. Also, it is to be understood that the phraseology and terminology used herein is for the purpose of description and should not be regarded as limiting. The use of “including,” “comprising,” or “having” and variations thereof herein is meant to encompass the items listed thereafter and equivalents thereof as well as additional items. Further, the present disclosure may use examples to illustrate one or more aspects thereof. Unless explicitly stated otherwise, the use or listing of one or more examples (which may be denoted by “for example,” “by way of example,” “e.g.,” “such as,” or similar language) is not intended to and does not limit the scope of the present disclosure.

[0062] The terms proximal and distal are used in this disclosure with their conventional medical meanings, proximal being closer to the operator or user of the system, and further from the region of surgical interest in or on the patient, and distal being closer to the region of surgical interest in or on the patient, and further from the operator or user of the system. [0063] Surgical procedures involving a cutting process (e.g., bone removal) using a robotic system use a multilayered approach to safety due to the automation of the cutting process. One identified risk during the cutting process is skiving of a surgical tool such as, for example, a cutting tool over the anatomical element (e.g., bone), leading to an application of an undesired force between a tip of the cutting tool held by, for example, a robot or a robotic arm and the anatomical element. The implications of such force may move the anatomical element and the tool, which may reduce an overall cutting accuracy and may also lead to cutting tool breakage. Contributing factor(s) to skiving are an approach angle of the cutting tool to the anatomical element during initial engagement, a cutting tool efficiency, a cutting tool sharpness, hardness of the bone tissue, and/or a rigidity between the robotic system and the anatomical element.

[0064] To mitigate the risk of skiving, systems and methods according to at least one embodiment of the present disclosure provide for both skive prevention, skive detection, and skive mitigation. At least one embodiment of skive prevention includes planning the cutting process to reduce an expected force applied on the cutting tool during the cutting process, thereby reducing the probability of skiving. Planning the cutting process may include planning an optimal approach cutting angle based on a surgical plan provided by a user such as the surgeon. The optimal approach cutting angle may be determined based on a normality of the cutting tool to the anatomical element and/or a shape of the cutting tool. At least one embodiment of skive detection and mitigation may include using one or more sensors to detect an occurrence of skiving, which may trigger a pause in the cutting process and/or generate a notification to the user (e.g., a surgeon). The one or more sensors may include, for example, torque meters or a force-torque sensor on the robot that can provide feedback to the robotic system. The sensors can be used to optimize a speed of the cutting tool and/or the robotic movement such that constant pressure is applied to the cutting tool.

[0065] Embodiments of the present disclosure provide technical solutions to one or more of the problems of (1) planning a cutting process to prevent skiving, (2) automatically detect skiving during a cutting process, and (3) automatically or semi- automatically mitigate skiving during a cutting process.

[0066] Turning first to Fig. 1, a block diagram of a system 100 according to at least one embodiment of the present disclosure is shown. The system 100 may be used to plan a cutting process to prevent skiving, to detect skiving during the cutting process, to mitigate skiving, and/or carry out one or more other aspects of one or more of the methods disclosed herein. The system 100 comprises a computing device 102, one or more imaging devices 112, one or more surgical tool(s) 136, a robot 114, a navigation system 118, a database 130, and/or a cloud or other network 134. Systems according to other embodiments of the present disclosure may comprise more or fewer components than the system 100. For example, the system 100 may not include the imaging device 112, the robot 114, the navigation system 118, one or more components of the computing device 102, the database 130, and/or the cloud 134.

[0067] The computing device 102 comprises a processor 104, a memory 106, a communication interface 108, and a user interface 110. Computing devices according to other embodiments of the present disclosure may comprise more or fewer components than the computing device 102.

[0068] The processor 104 of the computing device 102 may be any processor described herein or any similar processor. The processor 104 may be configured to execute instructions stored in the memory 106, which instructions may cause the processor 104 to carry out one or more computing steps utilizing or based on data received from the imaging device 112, a sensor 138 of the surgical tool 136 and/or the robot 114, the robot 114, the navigation system 118, the database 130, and/or the cloud 134.

[0069] The memory 106 may be or comprise RAM, DRAM, SDRAM, other solid-state memory, any memory described herein, or any other tangible, non-transitory memory for storing computer-readable data and/or instructions. The memory 106 may store information or data useful for completing, for example, any step of the methods 500, 600, and/or 700 described herein, or of any other methods. The memory 106 may store, for example, instructions and/or machine learning models that support one or more functions of the robot 114. For instance, the memory 106 may store content (e.g., instructions and/or machine learning models) that, when executed by the processor 104, enable image processing 120, segmentation 122, skive prevention planning 124, and skive detection 128.

[0070] The image processing 120 enables the processor 104 to process image data of an image (obtained from, for example, the imaging device 112, the database 130, and/or the cloud 134) for the purpose of, for example, identifying information about anatomical elements and/or objects depicted in the image. The image data may be a 3D model and/or 2D images. The information may comprise, for example, identification of hard tissue and/or soft tissues, a boundary between hard tissue and soft tissue, a boundary of hard tissue and/or soft tissue, identification of a surgical tool such as the surgical tool 136, etc. The image processing 120 may, for example, identify hard tissue, soft tissue, and/or a boundary of the hard tissue and/or soft tissue by determining a difference in or contrast between colors or grayscales of image pixels. For example, a boundary between the hard tissue and the soft tissue may be identified as a contrast between lighter pixels and darker pixels. The imaging processing 120 may also use segmentation 122, as described below. [0071] The segmentation 122 enables the processor 104 to segment the image data so as to identify individual objects and/or anatomical elements in the image. The segmentation 122 may enable the processor 104 to identify a boundary of an object or an anatomical element by using, for example, feature recognition. For example, the segmentation 122 may enable the processor 104 to identify a vertebra in image data. In other instances, the segmentation 122 may enable the processor 104 to identify a boundary of an object or an anatomical element by determining a difference in or contrast between colors or grayscales of image pixels.

[0072] The skive prevention planning 124 enables the processor 104 to receive image data (whether a 3D model and/or 2D images) and inputs about a desired cutting process to determine one or more parameters of the cutting process. The one or more parameters of the cutting process may be optimized so as prevent skiving of a surgical tool such as the surgical tool 136 used in the cutting process. The one or more parameters may include, for example, a cutting angle of the surgical tool 136, whether to use a side plunge or a side cut for the surgical tool 136, a cutting pressure, a cutting speed, a cutting depth, a cutting oscillation, and/or a robotic arm speed. The inputs may include, for example, information about a cutting plane on the 3D model. The processor 104 may receive other inputs to the skive prevention planning 124 such as, for example, information about the surgical tool 136 (e.g., dimension, size, type, shape), a desired side plunge and/or side cut, a desired cutting trajectory, etc.

[0073] The skive detection 126 enables the processor 104 to receive sensor data (from, for example, the sensor 138) to adjust at least one parameter of the surgical tool 136 based on the sensor data during the cutting process. The at least one parameter may be adjusted when potential skiving of the surgical tool 136 is detected. The sensor data may include, for example, a pose of the surgical tool 136, a force exerted on the surgical tool 136, and/or a torque exerted on the surgical tool 136. Adjusting the at least one parameter may include, for example, adjusting the cutting angle of the surgical tool 136 based on a normality of the surgical tool 136 to a target anatomical element and a shape of the surgical tool 136, adjusting the cutting speed and the robotic arm speed based on the torque data and the force data, and/or adjusting the cutting oscillation and the robotic arm speed based on the force data. The skive detection 126 may also enable the processor 104 to stop operation of the surgical tool 136 and/or to generate a notification when the sensor data meets or exceeds a predetermined threshold (which may indicate, for example, a potential skiving of the surgical tool 136).

[0074] Such content, if provided as in instruction, may, in some embodiments, be organized into one or more applications, modules, packages, layers, or engines. Alternatively or additionally, the memory 106 may store other types of content or data (e.g., machine learning models, artificial neural networks, deep neural networks, etc.) that can be processed by the processor 104 to carry out the various method and features described herein. Thus, although various contents of memory 106 may be described as instructions, it should be appreciated that functionality described herein can be achieved through use of instructions, algorithms, and/or machine learning models. The data, algorithms, and/or instructions may cause the processor 104 to manipulate data stored in the memory 106 and/or received from or via the imaging device 112, the sensor 138, the robot 114, the database 130, and/or the cloud 134.

[0075] The computing device 102 may also comprise a communication interface 108. The communication interface 108 may be used for receiving image data, sensor data, or other information from an external source (such as the imaging device 112, the robot 114, the sensor 138, the navigation system 118, the database 130, the cloud 134, and/or any other system or component not part of the system 100), and/or for transmitting instructions, images, sensor data, or other information to an external system or device (e.g., another computing device 102, the imaging device 112, the robot 114, the sensor 138, the navigation system 118, the database 130, the cloud 134, and/or any other system or component not part of the system 100). The communication interface 108 may comprise one or more wired interfaces (e.g., a USB port, an Ethernet port, a Firewire port) and/or one or more wireless transceivers or interfaces (configured, for example, to transmit and/or receive information via one or more wireless communication protocols such as 802.11a/b/g/n, Bluetooth, NFC, ZigBee, and so forth). In some embodiments, the communication interface 108 may be useful for enabling the device 102 to communicate with one or more other processors 104 or computing devices 102, whether to reduce the time needed to accomplish a computing-intensive task or for any other reason.

[0076] The computing device 102 may also comprise one or more user interfaces 110. The user interface 110 may be or comprise a keyboard, mouse, trackball, monitor, television, screen, touchscreen, and/or any other device for receiving information from a user and/or for providing information to a user. The user interface 110 may be used, for example, to receive a user selection or other user input regarding any step of any method described herein. Notwithstanding the foregoing, any required input for any step of any method described herein may be generated automatically by the system 100 (e.g., by the processor 104 or another component of the system 100) or received by the system 100 from a source external to the system 100. In some embodiments, the user interface 110 may be useful to allow a surgeon or other user to modify instructions to be executed by the processor 104 according to one or more embodiments of the present disclosure, and/or to modify or adjust a setting of other information displayed on the user interface 110 or corresponding thereto.

[0077] Although the user interface 110 is shown as part of the computing device 102, in some embodiments, the computing device 102 may utilize a user interface 110 that is housed separately from one or more remaining components of the computing device 102. In some embodiments, the user interface 110 may be located proximate one or more other components of the computing device 102, while in other embodiments, the user interface 110 may be located remotely from one or more other components of the computer device 102.

[0078] The imaging device 112 may be operable to image anatomical feature(s) (e.g., a bone, veins, tissue, etc.) and/or other aspects of patient anatomy to yield image data (e.g., image data depicting or corresponding to a bone, veins, tissue, etc.). “Image data” as used herein refers to the data generated or captured by an imaging device 112, including in a machine-readable form, a graphical/visual form, and in any other form. In various examples, the image data may comprise data corresponding to an anatomical feature of a patient, or to a portion thereof. The image data may be or comprise a preoperative image, an intraoperative image, a postoperative image, or an image taken independently of any surgical procedure. In some embodiments, a first imaging device 112 may be used to obtain first image data (e.g., a first image) at a first time, and a second imaging device 112 may be used to obtain second image data (e.g., a second image) at a second time after the first time. The imaging device 112 may be capable of taking a 2D image or a 3D image to yield the image data. The imaging device 112 may be or comprise, for example, an ultrasound scanner (which may comprise, for example, a physically separate transducer and receiver, or a single ultrasound transceiver), an O-arm, a C-arm, a G-arm, or any other device utilizing X-ray -based imaging (e.g., a fluoroscope, a CT scanner, or other X-ray machine), a magnetic resonance imaging (MRI) scanner, an optical coherence tomography (OCT) scanner, an endoscope, a microscope, an optical camera, a thermographic camera (e.g., an infrared camera), a radar system (which may comprise, for example, a transmitter, a receiver, a processor, and one or more antennae), or any other imaging device 112 suitable for obtaining images of an anatomical feature of a patient. The imaging device 112 may be contained entirely within a single housing, or may comprise a transmitter/emitter and a receiver/detector that are in separate housings or are otherwise physically separated.

[0079] In some embodiments, the imaging device 112 may comprise more than one imaging device 112. For example, a first imaging device may provide first image data and/or a first image, and a second imaging device may provide second image data and/or a second image. In still other embodiments, the same imaging device may be used to provide both the first image data and the second image data, and/or any other image data described herein. The imaging device 112 may be operable to generate a stream of image data. For example, the imaging device 112 may be configured to operate with an open shutter, or with a shutter that continuously alternates between open and shut so as to capture successive images. For purposes of the present disclosure, unless specified otherwise, image data may be considered to be continuous and/or provided as an image data stream if the image data represents two or more frames per second.

[0080] The robot 114 may be any surgical robot or surgical robotic system. The robot 114 may be or comprise, for example, the Mazor X™ Stealth Edition robotic guidance system. The robot 114 may be configured to position the imaging device 112 at one or more precise position(s) and orientation(s), and/or to return the imaging device 112 to the same position(s) and orientation(s) at a later point in time. The robot 114 may additionally or alternatively be configured to manipulate a surgical tool (whether based on guidance from the navigation system 118 or not) to accomplish or to assist with a surgical task. In some embodiments, the robot 114 may be configured to hold and/or manipulate an anatomical element during or in connection with a surgical procedure. The robot 114 may comprise one or more robotic arms 116. In some embodiments, the robotic arm 116 may comprise a first robotic arm and a second robotic arm, though the robot 114 may comprise more than two robotic arms. In some embodiments, one or more of the robotic arms 116 may be used to hold and/or maneuver the imaging device 112. In embodiments where the imaging device 112 comprises two or more physically separate components (e.g., a transmitter and receiver), one robotic arm 116 may hold one such component, and another robotic arm 116 may hold another such component. Each robotic arm 116 may be positionable independently of the other robotic arm. The robotic arms 116 may be controlled in a single, shared coordinate space, or in separate coordinate spaces.

[0081] The robot 114, together with the robotic arm 116, may have, for example, one, two, three, four, five, six, seven, or more degrees of freedom. Further, the robotic arm 116 may be positioned or positionable in any pose, plane, and/or focal point. The pose includes a position and an orientation. As a result, an imaging device 112, surgical tool, or other object held by the robot 114 (or, more specifically, by the robotic arm 116) may be precisely positionable in one or more needed and specific positions and orientations.

[0082] Each robotic arm 116 may comprise one or more sensors 138. The one or more sensors 138 enable the processor 104 (or a processor of the robot 114) to determine a precise pose in space of the robotic arm (as well as any object or element held by or secured to the robotic arm), and/or to determine a force and/or torque exerted by or on the robotic arm 116. For example, where the robotic arm 116 comprises a hinge joint, a sensor 138 may detect an angular position of a robotic arm member extending from the hinge joint relative to an axis of the hinge joint. Where the robotic arm 116 comprises a rotary joint, the sensor 138 may detect an angular position of a robotic arm member relative to the axis that extends through the robotic arm member and the rotary joint. Each sensor 138 may be, for example, a rotary encoder, a linear encoder, or an incremental encoder. Each sensor may also be or include a force sensor, a pressure sensor, a torque sensor, and/or a current sensor. Sensor data from the sensors 138 may be provided, for example, to a processor of the robot 114, to the processor 104 of the computing device 102, and/or to the navigation system 118. The data may be used in connection with one or more aspects of one or more methods disclosed herein.

[0083] In some embodiments, reference markers (e.g., navigation markers) may be placed on the robot 114 (including, e.g., on the robotic arm 116), the imaging device 112, or any other object in the surgical space. The reference markers may be tracked by the navigation system 118, and the results of the tracking may be used by the robot 114 and/or by an operator of the system 100 or any component thereof. In some embodiments, the navigation system 118 can be used to track other components of the system (e.g., imaging device 112) and the system can operate without the use of the robot 114 (e.g., with the surgeon manually manipulating the imaging device 112 and/or one or more surgical tools, based on information and/or instructions generated by the navigation system 118, for example). [0084] The navigation system 118 may provide navigation for a surgeon and/or a surgical robot during an operation. The navigation system 118 may be any now-known or future-developed navigation system, including, for example, the Medtronic

Stealth Station™ S8 surgical navigation system or any successor thereof. The navigation system 118 may include one or more cameras or other sensor(s) for tracking one or more reference markers, navigated trackers, or other objects within the operating room or other room in which some or all of the system 100 is located. The one or more cameras may be optical cameras, infrared cameras, or other cameras. In some embodiments, the navigation system 118 may comprise one or more electromagnetic sensors. In various embodiments, the navigation system 118 may be used to track a position and orientation (e.g., a pose) of the imaging device 112, the robot 114 and/or robotic arm 116, and/or one or more surgical tools (or, more particularly, to track a pose of a navigated tracker attached, directly or indirectly, in fixed relation to the one or more of the foregoing). The navigation system 118 may include a display for displaying one or more images from an external source (e.g., the computing device 102, imaging device 112, or other source) or for displaying an image and/or video stream from the one or more cameras or other sensors of the navigation system 118. In some embodiments, the system 100 can operate without the use of the navigation system 118. The navigation system 118 may be configured to provide guidance to a surgeon or other user of the system 100 or a component thereof, to the robot 114, or to any other element of the system 100 regarding, for example, a pose of one or more anatomical elements, whether or not a tool is in the proper trajectory, and/or how to move a tool into the proper trajectory to carry out a surgical task according to a preoperative or other surgical plan.

[0085] The surgical tool 136 may be or comprise any surgical tool for which skiving is or may be a concern during use, including, for example, a drill or any cutting tool. The surgical tool 136 in some embodiments may include an ultrasonic cutting tool or an oscillating cutting tool. The surgical tool 136 may be configured to be supported and operated manually; to be supported robotically but operated manually; and/or to be supported and operated robotically. The surgical tool 136 may comprise one or more sensors 138, which were described above. Such sensors 138 may detect, for example, one or more forces or torques exerted on or by the surgical tool 136; current consumed by the surgical tool 136; and/or a position of one or more components of the surgical tool 136 relative to one or more other components of the surgical tool 136. [0086] The database 130 may store information that correlates one coordinate system to another (e.g., one or more robotic coordinate systems to a patient coordinate system and/or to a navigation coordinate system). The database 130 may additionally or alternatively store, for example, one or more surgical plans (including, for example, pose information about a target and/or image information about a patient’s anatomy at and/or proximate the surgical site, for use by the robot 114, the navigation system 118, and/or a user of the computing device 102 or of the system 100); one or more images useful in connection with a surgery to be completed by or with the assistance of one or more other components of the system 100; and/or any other useful information. The database 130 may be configured to provide any such information to the computing device 102 or to any other device of the system 100 or external to the system 100, whether directly or via the cloud 134. In some embodiments, the database 130 may be or comprise part of a hospital image storage system, such as a picture archiving and communication system (PACS), a health information system (HIS), and/or another system for collecting, storing, managing, and/or transmitting electronic medical records including image data.

[0087] The cloud 134 may be or represent the Internet or any other wide area network. The computing device 102 may be connected to the cloud 134 via the communication interface 108, using a wired connection, a wireless connection, or both. In some embodiments, the computing device 102 may communicate with the database 130 and/or an external device (e.g., a computing device) via the cloud 134.

[0088] The system 100 or similar systems may be used, for example, to carry out one or more aspects of any of the methods 500, 600, and/or 700 described herein. The system 100 or similar systems may also be used for other purposes.

[0089] Figs. 2A-2B each illustrate a 3D model of an anatomical element 200 and a cutting plane 202 used in, for example, planning a cutting process. As previously described, the skive prevention planning 124 may enable the processor 104 to receive the 3D model of the anatomical element 200 and one or more inputs about a desired cutting process to determine one or more parameters of the cutting process. The one or more inputs may include information about a target anatomical element 200 (e.g., type of anatomical element (hard tissue or soft tissue), density of the anatomical element, etc.), information about the surgical tool 136 (e.g., type of surgical tool, shape of the surgical tool, size of the surgical tool, etc.), information about a cutting trajectory or path, and/or information about the cutting plane 202. The information about the cutting plane 202 may include, for example, information about a safety margin limit 204 and/or a no fly zone 208. The safety margin limit 204 may be a desired depth to which the surgical tool 136 may cut to within the anatomical element 200 that leaves a layer of the anatomical element 200 left. Such layer may prevent the surgical tool 136 from contacting or reaching an end 206 of the anatomical element 200 and from reaching the no fly zone 208.

[0090] As previously described, the one or more parameters may include, for example, a cutting depth, a cutting angle of the surgical tool (shown in Figs. 3 A-3B), whether to use a side plunge or a side cut for the surgical tool (shown in Figs. 4A-4B), a cutting pressure, a cutting speed, a cutting oscillation, and/or a robotic arm speed. Figs. 3 A-3B illustrate a first cutting angle and a second cutting angle, respectively. The first cutting angle of the surgical tool 136 may be an initial cutting angle received as input into the skive prevention planning 124. In other embodiments the first cutting angle may simply be a default cutting angle. As shown in Fig. 3A, the first cutting angle of the surgical tool 136 may not be normal to the cutting plane 202 of the anatomical element. Thus, the skive prevention planning 124 may adjust the cutting angle from the first cutting angle shown in Fig. 3 A to the second cutting angle in Fig. 3B such that the surgical tool 136 is normal to the cutting plane 202.

[0091] Figs. 4A-4B illustrate an example plunge cut and an example side cut, respectively. The skive prevention planning 124 may select the plunge cut, shown in Fig. 4A, the side cut, shown in Fig. 4B, or a combination of the plunge cut and the side cut for the cutting process. Alternatively or additionally, a user such as, for example, a surgeon or other medical provider may provide input for the plunge cut, the side cut, or the combination of the plunge cut and the side cut. The plunge cut may include removing hard tissue and/or soft tissue from the anatomical element by plunging the surgical tool 136 into the anatomical element in the direction of arrows 400A, 400B to a depth. The surgical tool 136 can be oscillated and moved by, for example, the robotic arm 116. The surgical tool 136 can then be moved in the direction of the arrow 402 and plunged again in a new location to remove hard tissue and/or soft tissue. Forces experienced by the surgical tool 136 can be monitored by the sensor 138 such that if the force exceeds a predetermined threshold, the robotic arm 116 may stop the surgical tool 136 or one or more parameters of the cutting process may be adjusted.

[0092] The side cut may include removing hard tissue and/or soft tissue from the anatomical element 200 by plunging the surgical tool 136 to a depth as represented by the arrow 404, then laterally moving the surgical tool 136 in the direction of the arrows 406 A, 406B to remove a layer of the anatomical element 200. After the layer is removed, the surgical tool 136 can be plunged to another depth and laterally moved to remove another layer of the anatomical element 200. During the side cut, torque and/or force experienced by the surgical tool 136 can be monitoring by the sensor 138 to determine if the surgical tool 136 is experiencing resistance from the hard tissue. If the surgical tool 136 is experiencing resistance, the speed of the surgical tool can be increased and a speed of the robotic arm can be decreased. Such adjustments can be used to maintain a constant opposing force to a cutting vector by controlling a speed and/or oscillation of the surgical tool 136 and a speed of the robotic arm 116. Further, in instances where the force exceeds a predetermined threshold, the surgical tool 136 may be stopped and/or a notification may be generated to prevent damage to the anatomical element and/or the surgical tool 136. [0093] The inputs to the cutting process and the parameters of the cutting process described above are example inputs and parameters. It will be appreciated that in other embodiments, the inputs and the parameters may include more inputs and more parameters or less inputs and less parameters.

[0094] Fig. 5 depicts a method 500 that may be used, for example, for planning a cutting process to prevent skiving.

[0095] The method 500 (and/or one or more steps thereof) may be carried out or otherwise performed, for example, by at least one processor. The at least one processor may be the same as or similar to the processor(s) 104 of the computing device 102 described above. The at least one processor may be part of a robot (such as a robot 114) or part of a navigation system (such as a navigation system 118). A processor other than any processor described herein may also be used to execute the method 500. The at least one processor may perform the method 500 by executing elements stored in a memory such as the memory 106. The elements stored in memory and executed by the processor may cause the processor to execute one or more steps of a function as shown in method 500. One or more portions of a method 500 may be performed by the processor executing any of the contents of memory, such as an image processing 120, a segmentation 122, a skive prevention planning 124, and/or a skive detection 128.

[0096] The method 500 comprises receiving a 3D model of a target anatomical model (step 504). The 3D model of the anatomical element may be the same as or similar to the 3D model of the anatomical element 200. The 3D model may be a CT scan, an MRI scan, or a 3D model obtained using any other imaging modality. In some embodiments, the information may alternatively correspond to a plurality of 2D images of the anatomical portion of the patient, from which a 3D image or model may be generated. The anatomical portion of the patient is any anatomical portion of the patient that is relevant to a planned surgical procedure and cutting process. In some embodiments, the anatomical portion of the patient is a single anatomical element that is the target of the surgical procedure, while in other embodiments, the anatomical portion of the patient includes both a target one or more anatomical elements as well as surrounding anatomy (e.g., for a spinal surgery, the anatomical portion of the patient may comprise the patient’s torso). The information may be received, for example, from and/or via a memory such as the memory 106, a communication interface such as the communication interface 108, a user interface such as the user interface 110, an imaging device such as the imaging device 112 (e.g., an imaging device that generated the 3D image), a database such as the database 130, and/or a network such as the cloud 134. A processor such as the processor 104 using an image processing such as the image processing 120 may process the 3D image so as to identify anatomical elements in the 3D image and/or to take measurements of identified anatomical elements in the 3D model. As previously described, the imaging processing may use a segmentation such as the segmentation 122 to identify the anatomical elements in the 3D model.

[0097] The method 500 also comprises receiving inputs for a cutting process (step 508). The inputs may include information about a cutting plane, information about the surgical tool, information about the target anatomical element (e.g., type of anatomical element, whether the anatomical element is hard tissue or soft tissue, etc.), desired parameters of the cutting process, etc. The information about a cutting plane (which may be the same as or similar to the cutting plane 202) may be received from, for example, a user such as a surgeon, medical provider, or any other user. The information may include a desired cutting plane on the 3D model. The information may also include information about a safety margin limit such as the safety margin layer 204 and/or a no fly zone such as the no fly zone 208. The safety margin limit may be a desired depth to which the surgical tool may cut to within the anatomical element that leaves a layer of the anatomical element left. Such layer may prevent the surgical tool from contacting or reaching the no fly zone, which is the zone in which the surgical tool does not contact.

[0098] The method 500 also comprises determining one or more parameters of the cutting process (step 512). The one or more parameters may be determined by a processor such as the processor 104 using a skive prevention planning such as the skive prevention planning 124 to determine one or more parameters of the cutting process. The skive prevention planning enables the processor to receive image data (such as, for example, the 3D model received in the step 504) and information about a cutting plane on the 3D model (such as the information about the cutting plane received in the step 508). The one or more parameters of the cutting process may be optimized so as prevent skiving of the surgical tool used in the cutting process. The one or more parameters may include, for example, a cutting depth, a cutting angle of the surgical tool, whether to use a side plunge or a side cut for the surgical tool, a cutting pressure, a cutting speed, a cutting oscillation, and/or a robotic arm speed. The processor may receive other inputs to the skive prevention planning such as, for example, information about the surgical tool 136 (e.g., dimension, size, type, shape), a desired side plunge and/or side cut, a desired cutting trajectory, etc. [0099] The method 500 also comprises receiving user input (step 516). The user input may include, for example, approval, rejection, or one or more adjustments of the one or more parameters of the cutting process. The one or more parameters of the cutting process and/or steps of the cutting process may be displayed on, for example, a user interface such as the user interface 110. The user input may also be received through the user interface. In embodiments where the user input is a rejection of the one or more parameters, the steps 504, 508, and/or 512 may be repeated. For example, new inputs such as a different surgical tool may be received as input in the step 508 and the step 512 may be executed again to provide new parameters of the cutting process based on the different surgical tool. [0100] The present disclosure encompasses embodiments of the method 500 that comprise more or fewer steps than those described above, and/or one or more steps that are different than the steps described above.

[0101] Fig. 6 depicts a method 600 that may be used, for example, detecting and preventing skiving during a cutting process.

[0102] The method 600 (and/or one or more steps thereof) may be carried out or otherwise performed, for example, by at least one processor. The at least one processor may be the same as or similar to the processor(s) 104 of the computing device 102 described above. The at least one processor may be part of a robot (such as a robot 114) or part of a navigation system (such as a navigation system 118). A processor other than any processor described herein may also be used to execute the method 600. The at least one processor may perform the method 600 by executing elements stored in a memory such as the memory 106. The elements stored in memory and executed by the processor may cause the processor to execute one or more steps of a function as shown in method 600. One or more portions of a method 600 may be performed by the processor executing any of the contents of memory, such as an image processing 120, a segmentation 122, a skive prevention planning 124, and/or a skive detection 128.

[0103] The method 600 comprises causing a robotic arm to operate a surgical tool (step 604). The surgical tool may be the same as or similar to the surgical tool 136. The surgical tool may be or comprise any surgical tool for which skiving is or may be a concern during use, including, for example, a drill or any cutting tool. The surgical tool in some embodiments may include an ultrasonic cutting tool or an oscillating cutting tool. The surgical tool may be configured to be supported and operated manually; to be supported robotically but operated manually; and/or to be supported and operated robotically. In embodiments where the surgical tool is supported and/or operated robotically, a robot such as the robot 114 and a robotic arm such as the robotic arm 116 may orient, support, and/or operate the surgical tool. The surgical tool may comprise one or more sensors such as the sensor 138, which were described above. Such sensors may detect, for example, one or more forces or torques exerted on or by the surgical tool; current consumed by the surgical tool; and/or a position of one or more components of the surgical tool relative to one or more other components of the surgical tool.

[0104] The robotic arm may automatically operate the surgical tool in accordance with, for example, a surgical plan. The surgical plan may include the cutting process generated and planned in, for example, the method 500 described above.

[0105] The method 600 also comprises receiving sensor data from at least one sensor (step 608). The at least one sensor may be the same as or similar to the sensor 138. Each robotic arm may comprise the one or more sensors. The one or more sensors enable a processor such as the processor 104 (or a processor of the robot) to determine a precise pose in space of the robotic arm (as well as any object or element held by or secured to the robotic arm), and/or to determine a force and/or torque exerted by or on the robotic arm. Each sensor may be, for example, a rotary encoder, a linear encoder, or an incremental encoder. Each sensor may also be or include a force sensor, a pressure sensor, a torque sensor, and/or a current sensor. Sensor data from the sensors may be provided, for example, to a processor of the robot, to the processor of a computing device such as the computing device, and/or to a navigation system such as the navigation system 118. The surgical tool may also comprise the one or more sensors. Such sensors may detect, for example, one or more forces or torques exerted on or by the surgical tool; current consumed by the surgical tool; and/or a position of one or more components of the surgical tool relative to one or more other components of the surgical tool. [0106] The method 600 also comprises adjusting at least one parameter of the surgical tool (step 612). The at least one parameter of the cutting tool may be adjusted by, for example, a processor such as the processor 104 using a skive detection such as the skive detection 126. The skive detection enables the processor to use the sensor data (received in, for example, the step 608) to adjust at least one parameter of the surgical tool based on the sensor data. The at least one parameter may be adjusted when potential skiving of the surgical tool is detected. The sensor data may include, for example, a pose of the surgical tool, a force exerted on the surgical tool, and/or a torque exerted on the surgical tool Adjusting the at least one parameter may include, for example, adjusting the cutting angle of the surgical tool based on a normality of the surgical tool to a target anatomical element and a shape of the surgical tool, adjusting the cutting speed and the robotic arm speed based on the torque data and the force data, and/or adjusting the cutting oscillation and the robotic arm speed based on the force data.

[0107] The method 600 also comprises causing the robotic arm to stop operating the surgical tool (step 616). The robotic arm may stop orienting and/or operating the surgical tool when the cutting process is complete. Additionally or alternatively, the robotic arm may stop orienting and/or operating the surgical tool when potential skiving of the surgical tool is detected. Such potential skiving may be detected by, for example, the skive detection. More specifically, the potential skive may be detected when the torque and/or force is meets or exceeds a predetermined threshold. In such instances, when adjusting at least one parameter as described in the step 612 above may not prevent skiving, operation of the surgical tool may be stopped instead to prevent damage to the anatomical element and/or the surgical tool. Stopping the surgical tool may include sending instructions to the robotic arm and the robot to stop the surgical tool and/or receiving input from a user such as, for example, a surgeon or other medical provider to stop the surgical tool.

[0108] The method 600 also comprises generating a notification when the sensor data meets or exceeds a predetermined threshold (step 620). The notification may be a visual notification, an audible notification, or any type of notification communicated to a user. The notification may be communicated to the user via a user interface such as the user interface 110. In some embodiments, the notification may be automatically generated by the processor. In other embodiments, the notification may be automatically generated by any component of a system such as the system 100. In some embodiments, the notification is based whether the sensor data such as, for example, force data and/or torque data meets or exceeds a predetermined threshold. The predetermined threshold may correlate to a maximum allowable force and/or torque exerted on the surgical tool before a risk of skiving may occur. The predetermined threshold may be determined automatically using artificial intelligence and training data (e.g., historical cases) in some embodiments. In other embodiments, the predetermined threshold may be or comprise, or be based on, surgeon input received via the user interface. In further embodiments, the predetermined threshold may be determined automatically using artificial intelligence, and may thereafter be reviewed and approved (or modified) by a surgeon or other user. In examples where the predetermined threshold comprises a plurality of predetermined threshold, a notification may be generated when each predetermined threshold is met or exceeded. The notification may alert a surgeon or user of an expected force and/or torque experienced by the surgical tool that the surgeon or other user may wish to avoid or otherwise mitigate.

[0109] The present disclosure encompasses embodiments of the method 600 that comprise more or fewer steps than those described above, and/or one or more steps that are different than the steps described above.

[0110] Figs. 7-13C will be discussed together. Fig. 7 depicts a method 700 that may be used, for example, for generating and/or updating a cutting path based on skive indication. [OHl] The method 700 (and/or one or more steps thereof) may be carried out or otherwise performed, for example, by at least one processor. The at least one processor may be the same as or similar to the processor(s) 104 of the computing device 102 described above. The at least one processor may be part of a robot (such as a robot 114) or part of a navigation system (such as a navigation system 118). A processor other than any processor described herein may also be used to execute the method 700. The at least one processor may perform the method 700 by executing elements stored in a memory such as the memory 106. The elements stored in memory and executed by the processor may cause the processor to execute one or more steps of a function as shown in method 700. One or more portions of a method 700 may be performed by the processor executing any of the contents of memory, such as an image processing 120, a segmentation 122, a skive prevention planning 124, and/or a skive detection 128.

[0112] The method 700 comprises predicting or indicating skiving of a surgical tool (step 704). The skiving of the surgical tool (which may be the same as or similar to the surgical tool 136) may be predicted based on a planned cutting process that is planned using, for example, the method 500 described above. Predicting or indicating that skiving may occur with the surgical tool may include viewing (e.g., by a user such as a medical provider) or analyzing (e.g., automatically by, for example, a processor such as the processor 104) a planned cutting trajectory or path of the surgical tool in an axial view 800 or axial section view 802 of an anatomical element 804 (shown in Figs. 8A-8B, respectively), a lateral view 900 or lateral section view 902 of an anatomical element 904 (shown in Figs. 9A-9B, respectively), and/or an axial section view 1000 or isometric view 1002 of an anatomical element 1004 (shown in Figs. 10A-10B, respectively). The analysis to predict or indicate skiving may be used to inform a bone profile of a cutting area, path generation, and path planning as described below.

[0113] The method 700 also comprises determining a bone profile of a cutting area (step 708). The bone profile of a cutting area may include determining a cortical layer thickness 1100 of an anatomical element 1102 such as, for example, bone as shown in Fig. 11. The cortical layer may be determined by, for example, the processor using image processing such as the image processing 120 and/or segmentation such as the segmentation 122. The cortical layer thickness may be used, for example, for refining one or more parameters of the cutting path such as, for example, a vertical depth of the cutting path. In other words, the cortical layer thickness can be used to plan cutting paths with thinner slices so as to prevent skiving as cortical bone as compared to cancellous bone may have a higher tendency to skive. In some embodiments, the step 708 may be used in the step 716 to plan the cutting path.

[0114] The method 700 also comprises generating a cutting path (step 712). The cutting path may be generated by, for example, the processor. Generating the cutting path may include building the cutting path 1200 inside of the anatomical element 1202 (e.g., bone in some embodiments), as shown in Fig. 12. Generating the cutting path may take into account the skive indication predicted in the step 704 above. For example, in an area in which skiving may be likely or is highly likely to occur, the cutting area may be divided into smaller vertical cut(s) rather than a high vertical cut to avoid skiving.

[0115] The method 700 also comprises planning the cutting path (step 716). The step 716 may use, for example, the method 500 to plan the cutting path. The planning may include adjusting one or more parameters of the cutting path generated in the step 712. The planning may use, for example the step 708 to adjust or change the one or more parameters of the cutting path.

[0116] In some embodiments, the skive indication or prediction in the step 704 may be used to adjust, for example, an angle of an initial planned cutting angle of the surgical tool to avoid skiving. For example, as shown in Fig. 13A, the initial planned cutting angle 1300 relative to a normal angle of a cutting surface 1302 may be susceptible to skiving. Thus, the cutting angle may be modified to a modified cutting angle 1306 that is substantially or equal to the normal angle to prevent skiving.

[0117] In embodiments where the surgical tool has a ball-shaped cutting tip as shown in Fig. 13C, the planning may include determining different angles to orient and/or position the ball-shaped cutting tip on the anatomical element 1304 so as to prevent skiving. The planning may then move the surgical tool back to an initial or original angle as the surgical tool progresses along the cutting path.

[0118] The method 700 also comprises executing the cutting path using a robotic system (step 720). The cutting path may be executed using a robot such as the robot 114 and a robotic arm such as the robotic arm 116 supporting, orienting, and operating the surgical tool. The cutting path may be executed using, for example, the method 600 described above.

[0119] The method 700 also comprises detecting skiving of the surgical tool (step 724). The step 724 may be similar to the step 612 of the method 600 above in that a processor such as the processor 104 may use a skive detection such as the skive detection 126 to detect skiving of the surgical tool. The skive detection enables the processor to receive and analyze sensor data (e.g., force data, torque data, positional data, etc.) to detect skiving of the surgical tool. In some embodiments, the skive detection of the step 724 may be used to adjust the robotic execution of the step 720. For example, one or more parameters of the robotic execution such as, for example, an angle of the surgical tool, a rotational speed of the surgical tool, etc. may be adjusted when skive is detected in the step 724.

[0120] It will be appreciated that the method 700 may be used to update real-time planning (e.g., the steps 712 and/or 716) using skiving indication or prediction (e.g., the step 704). In other words, before skiving is actually detected in, for example, the step 724, the cutting path plan may be updated in the step 716 based on skive indication in the step 704. Thus, the cutting path plan may be adjusted when skiving is indicated but has not yet occurred to prevent skiving.

[0121] The present disclosure encompasses embodiments of the method 700 that comprise more or fewer steps than those described above, and/or one or more steps that are different than the steps described above.

[0122] As noted above, the present disclosure encompasses methods with fewer than all of the steps identified in Figs. 5-7 (and the corresponding description of the methods 500, 600, and 700), as well as methods that include additional steps beyond those identified in Figs. 5-7 (and the corresponding description of the methods 500, 600, and 700). The present disclosure also encompasses methods that comprise one or more steps from one method described herein, and one or more steps from another method described herein. Any correlation described herein may be or comprise a registration or any other correlation.

[0123] The foregoing is not intended to limit the disclosure to the form or forms disclosed herein. In the foregoing Detailed Description, for example, various features of the disclosure are grouped together in one or more aspects, embodiments, and/or configurations for the purpose of streamlining the disclosure. The features of the aspects, embodiments, and/or configurations of the disclosure may be combined in alternate aspects, embodiments, and/or configurations other than those discussed above. This method of disclosure is not to be interpreted as reflecting an intention that the claims require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed aspect, embodiment, and/or configuration. Thus, the following claims are hereby incorporated into this Detailed Description, with each claim standing on its own as a separate preferred embodiment of the disclosure.

[0124] Moreover, though the foregoing has included description of one or more aspects, embodiments, and/or configurations and certain variations and modifications, other variations, combinations, and modifications are within the scope of the disclosure, e.g., as may be within the skill and knowledge of those in the art, after understanding the present disclosure. It is intended to obtain rights which include alternative aspects, embodiments, and/or configurations to the extent permitted, including alternate, interchangeable and/or equivalent structures, functions, ranges or steps to those claimed, whether or not such alternate, interchangeable and/or equivalent structures, functions, ranges or steps are disclosed herein, and without intending to publicly dedicate any patentable subject matter.

Claims

CLAIMS What is claimed is:

1. A system for planning a cutting process to prevent skiving comprising: a processor; and a memory storing instructions for execution by the processor that, when executed, causes the processor to: receive a three-dimensional (3D) model of a target anatomical element; receive one or more inputs of the cutting process including a cutting plane; and determine one or more parameters of the cutting process based on the cutting plane and the 3D model.

2. The system of claim 1, wherein the memory stores further instructions for execution by the processor that, when executed, causes the processor to: receive input comprising at least one of an approval of the cutting process or an adjustment to the cutting process.

3. The system of claims 1 or 2, wherein determining the one or more parameters of the cutting process includes determining the cutting angle based on a normality to the target anatomical element and a shape of the surgical tool.

4. The system of any of the preceding claims, wherein determining the one or more parameters of the cutting process includes determining at least one of a plunge cut or side cut for the surgical tool.

5. The system of any of the preceding claims, wherein the information about the cutting plane on the 3D model is received as input from a user.

6. A system for preventing skiving during a cutting process comprising: a robotic arm configured to orient and operate a surgical tool; at least one sensor; a processor; and a memory storing instructions for execution by the processor that, when executed, cause the processor to: cause the robotic arm to operate the surgical tool; receive sensor data from the at least one sensor; and adjust at least one parameter of the surgical tool based on the sensor data.

7. The system of claim 6, wherein the at least one parameter comprises a cutting pressure, a cutting speed, a cutting oscillation, a cutting angle of the surgical tool, or a robotic arm speed.

8. The system of claims 6 or 7, wherein the at least one parameter comprises the cutting angle and the adjusting the cutting angle comprises determining the cutting angle based on a normality of the surgical tool to a target anatomical element and a shape of the surgical tool.

9. The system of claim 8, wherein the normality of the surgical tool is determined from pose information of the surgical tool received from the robotic arm.

10. The system of claim 8, wherein the at least one parameter comprises the cutting angle and the adjusting the cutting angle comprises determining at least one of a plunge cut or side cut.

11. The system of claim 8, wherein the sensor data comprises torque data or force data.

12. The system of claim 11, wherein the cutting speed and the robotic arm speed are adjusted based on the torque data and the force data.

13. The system of claim 11, wherein the cutting oscillation and the robotic arm speed are adjusted based on the force data.

14. The system of claim 6, wherein the memory stores further instructions for execution by the processor that, when executed, causes the processor to: receive a three-dimensional (3D) model of a target anatomical element; receive one or more inputs of the cutting process including a cutting plane; and determine one or more parameters of the cutting process based on the cutting plane and the 3D model.

15. The system of any of the preceding claims, wherein the memory stores further instructions for execution by the processor that, when executed, causes the processor to: cause the robotic arm to stop operating the surgical tool when the sensor data meets or exceeds a predetermined threshold.

16. A system for planning a cutting process to prevent skiving comprising: a surgical tool; a robotic arm configured to orient and operate the surgical tool; at least one sensor; a processor; and a memory storing instructions for execution by the processor that, when executed, causes the processor to: receive a three-dimensional (3D) model of a target anatomical element; receive information about a cutting plane on the 3D model; determine skive indication on the 3D model, wherein the skive indication correlates to a likelihood that skiving will occur on the target anatomical element; and determine one or more parameters of the cutting process based on the cutting plane, the skive indication, and the 3D model.

17. The system of claim 16, wherein the sensor is positioned on at least one of the robotic arm or the surgical tool.

18. The system of claims 16 or 17, wherein the surgical tool comprises at least one of an ultrasonic cutting or an oscillating cutting tool.

19. The system of any of the preceding claims, wherein the at least one parameter comprises a cutting pressure, a cutting speed, a cutting oscillation, a cutting angle of the surgical tool, or a robotic arm speed.

20. The system of claim 19, wherein the at least one parameter comprises the cutting angle and the adjusting the cutting angle comprises determining the cutting angle based on a normality of the surgical tool to a target anatomical element and a shape of the surgical tool.