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WO2025042928A1 - Estimation de l'âge d'instruments chirurgicaux entraînés par câble - Google Patents

Estimation de l'âge d'instruments chirurgicaux entraînés par câble Download PDF

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Publication number
WO2025042928A1
WO2025042928A1 PCT/US2024/043127 US2024043127W WO2025042928A1 WO 2025042928 A1 WO2025042928 A1 WO 2025042928A1 US 2024043127 W US2024043127 W US 2024043127W WO 2025042928 A1 WO2025042928 A1 WO 2025042928A1
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WO
WIPO (PCT)
Prior art keywords
age
instrument
control system
cable
computer
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
PCT/US2024/043127
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English (en)
Inventor
Evan CHANG-SIU
Gabriel Brisson
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Intuitive Surgical Operations Inc
Original Assignee
Intuitive Surgical Operations Inc
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Filing date
Publication date
Application filed by Intuitive Surgical Operations Inc filed Critical Intuitive Surgical Operations Inc
Publication of WO2025042928A1 publication Critical patent/WO2025042928A1/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

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Classifications

    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/40—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/30—Surgical robots
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
    • A61B34/70—Manipulators specially adapted for use in surgery
    • A61B34/71—Manipulators operated by drive cable mechanisms

Definitions

  • the present disclosure is directed to age estimation of cable-driven surgical instruments. More particularly, the present disclosure is directed to generating an age estimation model for cable-driven surgical instruments and providing guidance to a user of surgical instruments based upon the instrument age.
  • the cables in cable-driven surgical instruments can fail during surgery with undesirable consequences such as nonintuitive motion, undesirable cutting, burns to unintended tissue, or other deleterious effects which may affect the quality of the surgical procedure and/or the health of the patient undergoing the surgery.
  • Determining the age of a surgical instrument based upon the amount of time it has been operated may not accurately assess its age.
  • a cable-driven instrument may have a plurality of cables which experience various amounts of wear compared to one another based upon how each cable is used throughout its lifetime.
  • a generalized age estimate for a surgical instrument which does not take into account usage of specific components, such as cables, can result in unnecessarily expiring an instrument which still has useful life remaining, or conversely incorrectly estimating an instrument has time left to be safely operated, when in fact it does not.
  • determining when an instrument is at, or approaching, an age indicative of imminent failure may have detrimental consequences. For example, if the estimated age of an instrument incorrectly predicts its expiration earlier than necessary, an operator of the surgical instrument may perceive it as a nuisance and/or could be required to interrupt a surgery at a critical time. If the estimated life is predicted to end too late, or not at all, a cable unexpectedly break could occur during a surgical procedure.
  • a computer-implemented method of generating a model may include obtaining one or more sets of experimental data indicative of one or more testing instruments being operated to expiration, wherein each testing instrument of the one or more testing instruments includes a distal end, a proximal end, a movable component at the distal end, an instrument control system at the proximal end, and a plurality of cables connecting the movable component and the instrument control system such that movement of the movable component is controlled by driving the instrument control system; generating an age determination model based on the one or more sets of experimental data, the age determination model configured to provide a change in instrument age of an operating instrument based on one or more sets of operational data associated with the operation of the operating instrument; and providing the age determination model to a control system of a robotic surgical system configured to control the operating instrument.
  • a computer-readable media storing instructions.
  • the instructions when executed by one or more processors, cause a system to obtain one or more sets of experimental data indicative of one or more testing instruments being operated to expiration, wherein each testing instrument of the one or more testing instruments includes a distal end, a proximal end, a movable component at the distal end, an instrument control system at the proximal end, and a plurality of cables connecting the movable component and the instrument control system such that movement of the movable component is controlled by driving the instrument control system; generate an age determination model based on the one or more sets of experimental data, the age determination model configured to provide a change in instrument age of an operating instrument based on one or more sets of operational data associated with the operation of the operating instrument; and provide the age determination model to a control system of a robotic surgical system configured to control the operating instrument.
  • a system for generating a model may include one or more processors and a non-transitory storage medium storing processorexecutable instructions that, when executed by the one or more processors, causes the system to obtain one or more sets of experimental data indicative of one or more testing instruments being operated to expiration, wherein each testing instrument of the one or more testing instruments includes a distal end, a proximal end, a movable component at the distal end, an instrument control system at the proximal end, and a plurality of cables connecting the movable component and the instrument control system such that movement of the movable component is controlled by driving the instrument control system; generate an age determination model based on the one or more sets of experimental data, the age determination model configured to provide a change in instrument age of an operating instrument based on one or more sets of operational data associated with the operation of the operating instrument; and provide the age determination model to a control system of a robotic surgical system configured to control the operating instrument.
  • the computer-implemented method may include obtaining operational data associated with the operation of the operating instrument; obtaining a change in the instrument age associated with the operating instrument by inputting the operational data into an age determination model; updating the stored instrument age of the operating instrument based on the obtained change in the instrument age; and performing a remedial action when the updated instrument age exceeds an instrument age threshold.
  • the instructions when executed by one or more processors, may cause the system to obtain operational data associated with the operation of the operating instrument; obtain a change in the instrument age associated with the operating instrument by inputting the operational data into an age determination model; update the stored instrument age of the operating instrument based on the obtained change in the instrument age; and perform a remedial action when the updated instrument age exceeds an instrument age threshold.
  • FIG. 1 A is a is a simplified diagram of an example computer-assisted system, according to various embodiments.
  • FIG. 2 is a diagrammatic illustration of a portion of a medical device for movable component adjustment, according to various embodiments.
  • FIG. 3 is a diagrammatic illustration of a portion of a testing instrument having an antagonist drive system, according to various embodiments.
  • FIG. 4 is a diagrammatic illustration of a portion of a medical device for movable component adjustment, according to various embodiments.
  • FIG. 5 is a diagrammatic illustration of a portion of a testing instrument having a paired capstan drive system, according to various embodiments.
  • FIG. 6 is a is a simplified diagram of a training server, according to various embodiments.
  • FIGS. 11 A is an example user interface indicating the age of an operating instrument at a point in time, according to various embodiments.
  • spatially relative terms such as “beneath”, “below”, “lower”, “above”, “upper”, “proximal”, “distal”, and the like — may be used to describe the relationship of one element or feature to another element or feature as illustrated in the figures. These spatially relative terms are intended to encompass different positions (i.e., translational placements) and orientations (i.e., rotational placements) of a device in use or operation in addition to the position and orientation shown in the figures. For example, if a device in the figures is turned over, elements described as “below” or “beneath” other elements or features would then be “above” or “over” the other elements or features.
  • the term “below” can encompass both positions and orientations of above and below.
  • a device may be otherwise oriented (e.g., rotated 90 degrees or at other orientations) and the spatially relative descriptors used herein interpreted accordingly.
  • descriptions of movement along (translation) and around (rotation) various axes include various spatial positions and orientations.
  • the combination of a body’s position and orientation define the body’s pose.
  • geometric terms such as “parallel”, “perpendicular”, “round”, or “square”, are not intended to require absolute mathematical precision, unless the context indicates otherwise. Instead, such geometric terms allow for variations due to manufacturing or equivalent functions. For example, if an element is described as “round” or “generally round,” a component that is not precisely circular (e.g., one that is slightly oblong or is a many-sided polygon) is still encompassed by this description.
  • member refers to a constituent portion of a larger structure or mechanism.
  • a “member” can refer to an individual contiguous structure or multiple connected structures such as a mechanism.
  • da Vinci® surgical systems e.g., the Model IS4000, the Model IS3000, the Model IS2000, the Model IS 1200, the Model SP1099
  • inventive aspects may be embodied and implemented in both relatively smaller, hand-held, hand-operated devices that are not mechanically grounded in a world reference frame and relatively larger systems that have additional mechanical support that is grounded in a world reference frame.
  • embodiments disclosed herein may be implemented in a medical surgical system, the techniques disclosed herein may be applied to other manipulator systems applied to non-medical contexts.
  • an instrument may include a single cable coupled to a first drive member at a proximal end of the instrument that is coupled to a wrist of a movable component at a distal end of the instrument and returns to a second drive member at the proximal end of the instrument.
  • each proximal portion of the cable is associated with its own age. That is, a single cable may have a first age for the proximal portion between the first drive member and the movable component and a second age for the proximal portion between the second drive member and the movable component.
  • a first proximal portion of the cable may be referred to as a “first cable” and a the second proximal portion of the cable may be referred to as a “second cable,” despite the “first cable” and “second cable” being part of the same contiguous cable.
  • first cable a first proximal portion of the cable
  • second cable a second proximal portion of the cable
  • the age of a cable is sometimes used herein as shorthand for the age of a proximal portion of a cable.
  • Embodiments described herein generally refer to age as being normalized to a scale of 0 representing an unused cable and 100 being a cable that has just failed. It should be appreciated that in other embodiments, other scales for age may be utilized.
  • a display device 112 is also included in the workstation 102.
  • the display device 112 may be configured to display images for viewing by the operator 108.
  • the display device 112 can be moved in various degrees of freedom (DOFs) to accommodate the viewing position of the operator 108 and/or to provide control functions.
  • the leader input devices 106 may include the display device 112.
  • displayed images may depict a worksite at which the operator 108 is performing various tasks by manipulating the leader input devices 106 and/or the display device 112.
  • images displayed by display device 112 may be received by the workstation 102 from one or more imaging devices arranged at a worksite.
  • the images displayed by the display device 112 may be generated by the display device 112 (or by a different connected device or system), such as for virtual representations of tools, the worksite, or for user interface components.
  • the operator 108 can sit in a chair or other support in front of the workstation 102, position his or her eyes in front of the display device 112, manipulate the leader input devices 106, and rest his or her forearms on the ergonomic support 110 as desired.
  • the operator 108 can stand at the workstation or assume other poses, and the display device 112 and the leader input devices 106 can be adjusted in position (height, depth, etc.) to accommodate the pose of the operator 108.
  • the one or more leader input devices 106 can be ungrounded (ungrounded leader input devices being not kinematically grounded, such as leader input devices 106 held by the hands of the operator 108 without additional physical support). Such ungrounded leader input devices 106 can be used in conjunction with the display device 112.
  • the display device 112 is positioned near the worksite such that the operator 108 can manually operate instruments at the worksite, such as a medical instrument in a medical example, while viewing images displayed by the display device 112.
  • the repositionable structures 120 may include a plurality of links that are rigid members and joints that can be individually actuated as part of a kinematic series. Additionally, each of the repositionable structures 120 is configured to couple to an instrument 122. While Figure 1 illustrates a follower device 104 that has four repositionable structures 120, in other embodiments, the follower device 104 may include one, two, three, four, five, six, or additional or fewer repositionable structures 120.
  • the instrument 122 can include, for example, a working portion 126 (also referred to herein as a “movable component”) and one or more structures for supporting and/or driving the working portion 126.
  • Example working portions 126 include end effectors that physically contact or manipulate material, energy application elements that apply electrical, RF, ultrasonic, or other types of energy, sensors that detect characteristics of the workspace environment (such as temperature sensors, imaging devices, etc.), and the like.
  • each instrument 122 may be mounted to a portion of a respective repositionable structure 120. In FIG. 1A, this is shown with the drive assembly 130 physically coupled to the transmission mechanism 128.
  • the distal portion of each repositionable structure 120 further includes a cannula mount 124 to which a cannula (not shown) is mounted. When a cannula is mounted to the cannula mount 124, a shaft of the instrument 122 passes through the cannula and into a workspace.
  • the instrument 122 can be, or include, an instrument used to perform medical (e.g., surgical, diagnostic, and/or therapeutic) or nonmedical procedures (e.g., industrial inspection applications).
  • the instrument 122 includes a shaft 103 elongated along a longitudinal axis A , between proximal end portion 105 and distal end portion 107.
  • the shaft 103 is on the order of a few millimeters in diameter, for example from five to eight millimeters in diameter.
  • the instrument 122 further includes a working portion 126 coupled to the distal end portion 107 and a force transmission system 111 (only the exterior housing portion of which is depicted) coupled to the proximal end portion 105.
  • the working portion 126 is configured to carry out a medical or non-medical (such as industrial) procedure.
  • the working portion 126 by one or more types of tools such as gripping tools, staplers, shears, ligation clip appliers, electrosurgical tools, ultrasonic tools, suturing tools, translating sleds, translating cutting tools, or other types of tools. While the illustration of FIG.
  • FIG. 1 B depicts an working portion 126 having jaw members 113 configured to move toward and away from each other (either by one or both jaw members pivoting about a pivot axis), such a configuration is exemplary and non-limiting and those of ordinary skill in the art would appreciate the instrument 122 can have any of a variety of end effectors coupled to the working portion 126 without departing from the scope of the present disclosure.
  • the instrument 122 further optionally includes an articulable component 115 coupling the working portion 126 to the shaft 103.
  • the articulable structure 115 can be positioned along the distal end portion 107 of the shaft 103. But the disclosure is not so limited and the articulable structure 115 can be positioned at any location along the shaft 103 without limitation.
  • the instrument 122 can include more than one articulable structure 115, such as two, three, or more articulable structures located in series or at multiple spaced apart locations along the length of the shaft 103.
  • the articulable structure 115 can be controlled and actuated via actuation members (not illustrated in FIG.
  • an articulable structure can serve as a wrist mechanism supporting and coupling the working portion 126 to the shaft 103 so as to allow orientation of the working portion 126 relative to the shaft in pitch and/or yaw.
  • the force transmission system 111 is coupled to the proximal end portion 105 of the shaft 103.
  • the force transmission system 111 may be coupled at various locations along the shaft 103, and in some cases moveable along the shaft, but generally in a position such that it remains external to a remote site (such as a patient’s body) at which the working portion 126 and a distal end portion 107 of the shaft 103 are inserted to perform a procedure, thereby permitting access to manipulate inputs on the force transmission system 111.
  • Force transmission system 111 includes a housing 117 supporting an input drive portion 119.
  • Input drive portion 119 includes a drive interface 121.
  • Drive interface 121 provides mechanical connections to the other control features of force transmission system 111 , such as various output drives configured to be operated to transmit force to control the moveable components and operations at the distal end portion 107 of the instrument 122.
  • drive interface 121 is configured to be coupled to a manipulator system.
  • the repositionable structures 120 and/or instrument 122 can be controlled to move the working portion 126 in response to manipulation of the leader input devices 106 by the operator 108. Accordingly, the repositionable structures 120 and/or instrument 122 may be said to “follow” the leader input devices 106 through teleoperation. This enables the operator 108 to perform tasks at the worksite using the repositionable structures 120 and/or instrument 122. For a surgical example, the operator 108 can direct the repositionable structures 120 of the follower device 104 to move the working portions 126 as part of a surgical procedure performed at an internal surgical site that is entered via one or more minimally invasive apertures or natural orifices.
  • the control system 140 includes a processor system 150 and a memory 160.
  • the memory 160 may store a control module 170.
  • the processor system 150 may include one or more processors having different processing architectures for processing instructions.
  • the one or more processors may be one or more cores or microcores of a multi-core processor, a central processing unit (CPU), a microprocessor, a field- programmable gate array (FPGA), an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a graphics processing unit (GPU), a tensor processing unit (TPU), and/or the like.
  • the processor system 150 includes circuity to support one or more communication interfaces (e.g., Bluetooth interface, infrared interface, network interface, optical interface, etc.). Additionally, a communication interface of control system 140 may include an integrated circuit for connecting the control system 140 to a network (not shown) (e.g., a local area network (LAN), a wide area network (WAN) such as the Internet, mobile network, or any other type of network) and/or to another device, such as the workstation 102 and/or the follower device 104.
  • a network not shown
  • LAN local area network
  • WAN wide area network
  • the Internet such as the Internet
  • mobile network such as the workstation 102 and/or the follower device 104.
  • the memory 160 may include non-persistent storage (e.g., volatile memory, such as random access memory (RAM), cache memory), persistent storage (e.g., a hard disk, an optical drive such as a compact disk (CD) drive or digital versatile disk (DVD) drive, a flash memory, a floppy disk, a flexible disk, a magnetic tape, any other magnetic medium, any other optical medium, programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a FLASH-EPROM, and/or any other memory chip or cartridge.
  • non-persistent storage e.g., volatile memory, such as random access memory (RAM), cache memory
  • persistent storage e.g., a hard disk, an optical drive such as a compact disk (CD) drive or digital versatile disk (DVD) drive, a flash memory, a floppy disk, a flexible disk, a magnetic tape, any other magnetic medium, any other optical medium, programmable read-only memory (PROM), an
  • the non-persistent storage and persistent storage are examples of non- transitory, tangible machine-readable media that can store executable code that, when run by one or more processors (e.g., processor system 150), can cause the one or more processors to perform one or more of the techniques and/or methods disclosed herein.
  • processors e.g., processor system 150
  • control system 140 may also include one or more input devices (such as a touchscreen, keyboard, mouse, microphone, touchpad, electronic pen, or any other type of input device) and/or output devices (such as a display device, a speaker, external storage, a printer, or any other output device).
  • input devices such as a touchscreen, keyboard, mouse, microphone, touchpad, electronic pen, or any other type of input device
  • output devices such as a display device, a speaker, external storage, a printer, or any other output device.
  • the control system 140 may be implemented on a particular node of a distributed computing system (e.g., a cloud computing system).
  • different functionalities associated with the control system 140 may be implemented on different nodes of the distributed computing system.
  • one or more elements of the aforementioned control system 140 may be located at a remote location and connected to the other elements over a network.
  • Techniques disclosed herein relate to providing operator guidance on an estimated age of the instruments 122.
  • the system facilitating such a technique can make the procedure process easier for human operators, reduce workflow disruption, reduce time spent accounting for expired instruments, and increase the overall efficiency of the procedures.
  • the system may intervene to restrict usage of the instruments 122 based on the estimated age of the instruments 122 (e.g., by limiting a range of motion to reduce forces exerted upon the instruments 122), which may prevent the instruments 122 from expiring at an inopportune time during a procedure.
  • the system may extend the working lifetime of the instruments 122 when the instrument approaches a low-life state .
  • the disclosed techniques provide an improvement to the computer-assisted system 100 in the non-surgical aspects of the procedure, and can be used to improve computer-assisted systems applied in non-medical contexts.
  • the computer-assisted system 100 is operated in a testing mode of operation to generate experimental data used to train an age estimation model.
  • the instruments 122 may be referred to as “testing instruments.”
  • the computer-assisted system 100 may be operated in a scripted manner to generate experimental data such that a training server 180 is able to train an age estimation model based upon the experimental data generated by the computer- assisted system 100.
  • the memory 160 stores one or more scripts configured to generate control commands for the testing instruments 122. More particularly, the commands may be configured to set different control parameters of the testing instruments 122.
  • the control parameters may include commands that cause a drive member of the testing instruments to rotate in a particular manner (e.g., a speed and/or direction of the rotation of the drive member).
  • the scripted motion sets the control parameters to achieve a desired state of operational parameters associated with the testing instruments 122.
  • the operational parameters may include mechanical work, pitch, torque, velocity, acceleration, orientation, etc. It should be appreciated that when the instruments 122 are being controlled by the scripts executed by the control system 140, the control system 140 may disregard any inputs received by the leader input devices 106 such that motion of the instruments 122 is controlled entirely by the executed scripts.
  • the scripted motion may be configured to operate a testing instrument 122 to achieve a set of generally constant operational parameters until a cable of the testing instrument 122 has failed, resulting in the expiration of the testing instrument 122. It should be appreciated that due to the finite length of the cable, not all of the operational parameters can be maintained constant (e.g., velocity).
  • the scripted motion may drive the cable in a first direction to achieve a first set of constant operational parameters until a first end of the cable is reached, and then driving the cable in a reverse direction to achieve a second set of constant operational parameters until a second end of the cable is reached.
  • the one or more scripts may be designed to determine which operational parameters of the testing instruments 122 significantly impact the lifetime and/or the rate of age accumulation of the testing instruments 122.
  • the memory 160 may store different scripts that are configured to experimentally test the different operational parameters. More particularly, the memory 160 may store different scripts that have different values for a particular operational parameter under test, but the same values for other control operational parameters. The memory 160 may store different sets of scripts for each operational parameter being evaluated during the testing process. Accordingly, by executing different scripts, the control system 140 is able to compile a set of experimental data that is useful for deriving the relationship between the operational parameters when training an age determination model.
  • the memory 160 may also be configured to store one or more playback logs from a prior execution of a historical procedure using a computer- assisted system.
  • the playback logs may indicate a series of control commands issued by a control system during the historical procedure. Accordingly, when the control system 140 executes the playback log, the testing instruments 122 may be controlled in a similar manner (and experience similar stress) as the operating instruments that performed the historical procedure. As a result, the control system 140 is able to compile a set of experimental data that better models typical instrument usage patterns when training an age determination model.
  • the control system 140 may be configured to execute the scripts and/or a playback log from the memory 160. Additionally, the control system 140 may enable an operator to manually control operation of the testing instruments 122. When generating a set of experimental data, the control system 140 may periodically record sets of values for the operational parameters. For example, the control system 140 may record 2000 samples/second, 1100 samples/second, 5000 samples/second, 100 samples/second, etc. Regardless of the particular technique for generating the motion of the testing instrument 122, the control system 140 may perform, repeat, and/or cycle the motion until the testing instrument 122 fails.
  • control system 140 may compile the samples into a vector that represents the experimental data for the particular experiment associated with the scripted motion. The control system 140 may then transmit the sets of experimental data to the training server 180 to perform the training of the age determination model.
  • the computer-assisted system 100 is operated in an operating mode of operation where the follower device 104 is used to perform a procedure.
  • the instruments 122 may be referred to as “operating instruments.”
  • the control system 140 may obtain a trained age estimation model from the server 180 to determine the age of the operating instruments 122 as they are used to perform a procedure. More particularly, the control system 140 may be configured to periodically obtain sets of operational data associated with the operating instruments 122 to input the set of operational data into the age determination model to determine an amount of age accumulated by the operating instruments. It should be appreciated that the operating instruments 122 may generate different sets of operational data for each proximal portion of a cable included in the operating instrument 122.
  • control system 140 may track the age accumulated of each proximal portion separately.
  • the age of the operating instrument may be determined by a limiting cable (e.g., the proximal portion associated with a highest amount of accumulated age).
  • the control system 140 may convert the age of the proximal portions of the cables into an estimated time of use remaining to provide more meaningful feedback to an operator of the computer-assisted system 100.
  • the memory 160 may store models (also referred to as “profiles”) associated with operational data trends for different phases of the procedure being performed. Accordingly, the control system 140 may be able to use the stored model of the procedure as a prediction for expected future values of the operational data of the operating instruments 122. By inputting the expected future values into the age determination model, the control system 140 may be able to identify a point in time when the proximal portion of a cable is expected to fail.
  • the control system 140 may then estimate the time remaining based on a number of samples in the future when the cable is expected to fail. [0072]
  • the control system 140 is able to more accurately assess the age of the operating instruments 122 than techniques that assess the age of the operating instruments 122 as a whole.
  • the proximal portions of the cables may be subjected to different stresses at different phases of a procedure. Accordingly, the limiting cable may change throughout the course of the procedure.
  • tracking the age of each proximal end enables the control system 140 to adjust the estimation based on the actual limiting cable as it changes throughout the procedure. As a result, the age estimation techniques are more accurate enabling a more efficient execution of the procedure.
  • the memory 160 may be configured to store a model associated with an operator of the computer-assisted system 100.
  • the operator model may indicate operator-specific usage patterns that manifest in the operational data. For example, the operator model may indicate that the operator generally applies more torque on the operating instruments 122 than average (as indicated in the model of the procedure) or that the operator pitches cables faster than for other operators. Accordingly, when the control system 140 estimates the time remaining for an operating instrument 122, the control system 140 may adjust the values of the procedure model by respective factors derived from the operator model.
  • FIG. 2 is a schematic illustration of a portion of an instrument 2400 (such as one of the instruments 122) according to an embodiment.
  • the instrument 2400 includes a shaft 2410, a cable 2420, a movable component 2460 (such as the working portion 126), and an instrument control system 2700.
  • the instrument control system 2700 functions to receive one or more motor or manual input forces or torques and mechanically transmit the received forces or torques to move the movable component 2460.
  • one or more electric motors in a manipulator unit e.g., the follower device 104 can provide an input to the instrument control system 2700, which in turn transmits the input via the cable 2420 to control the movable component 2460.
  • the control system includes a chassis 2768, a first drive member 2710, a second drive member 2720, and a manual drive structure 2860.
  • the first tool drive member can be operable to produce rotational movement about the axis A3, and the second drive member 2720 can similarly be operable to produce rotational movement about an axis A4 parallel to the axis A3.
  • the first drive member 2710 can rotate in the direction of arrows DD and the second drive member 2720 can rotate in the direction of arrows EE in FIG. 2.
  • the second drive member 2720 can rotate independently about the axis A4 in either the same or the opposite direction (clockwise or counterclockwise).
  • each of the individual drive members rotates such that the desired individual cable pay-in or pay-out is performed to perform the desired movable component motion — grip, yaw, or pitch — either alone or in combination.
  • FIG. 3 depicts an example instrument 300 (such as the instruments 122, 2400) that includes two cables (such as cables 2420) configured in an antagonistic arrangement.
  • a first cable is configured such that a first proximal portion 311 a of the first cable is coupled to a first drive member 301 (such as the drive member 2710) and a second proximal portion 314a of the first cable is coupled to a second drive member 304 (such as the drive member 2720).
  • a second cable is configured such that a first proximal portion 312a of the first cable is coupled to a first drive member 302 (such as the drive member 2710) and a second proximal portion 313a of the first cable is coupled to a second drive member 303 (such as the drive member 2720).
  • first drive member 302 such as the drive member 2710
  • second proximal portion 313a of the first cable is coupled to a second drive member 303 (such as the drive member 2720).
  • FIG. 3 depicts the drive members 301-304 as disks, in other embodiments, other suitable drive member mechanisms may be implemented.
  • the control system 140 may be configured to generate commands to operate the drive members 301-304 to control the grip, pitch and/or yaw of the movable component.
  • the control system 140 may generate commands to cause the drive members 301 and 304 to rotate in a first direction and drive members 302 and 303 to rotate in the opposite direction.
  • the control system 140 may generate commands to cause the drive members 301 and 303 to rotate in a first direction and drive members 302 and 304 to rotate in the opposite direction.
  • the control system 140 may generate commands to cause the drive members 301 and 302 to rotate in a first direction and drive members 303 and 3034 to rotate in the opposite direction.
  • the instrument 3400 may just include the first drive member 2710 and the second drive member 2720, while omitting the manual drive structure 2860 and the corresponding manual drive components.
  • FIG. 5 depicts an example instrument 500 (such as the instruments 122, 3400) that includes three cables (such as cables 3420 or 3430) configured in a paired capstan arrangement.
  • a first cable is configured such that a first proximal portion 511a of the first cable is coupled to a first drive member 501 (such as the drive member 3710) and a second proximal portion 512a of the first cable is coupled to the first drive member 501 .
  • a second cable is configured such that a first proximal portion 513a of the second cable is coupled to a second drive member 502 (such as the drive member 3720) and a second proximal portion 514a of the second cable is coupled to the second drive member 502.
  • a third cable is configured such that a first proximal portion 515a of the third cable is coupled to a third drive member 503 and a second proximal portion 516a of the third cable is coupled to the third drive member 503. It should be appreciated that while FIG. 5 depicts the drive members 501-503 as disks, in other embodiments, other suitable drive member mechanisms may be implemented.
  • the first, second, and third cables are coupled to a wrist 522 configured to transfer motion of the cables to control movement of tool members 524 (such as the tool member 2462) of a movable component (such as the working portion 126 or the movable component 2460). More particularly, the distal portions 511b and 512b of the first cable form a first cable couplet coupling the first cable to the movable component, the distal portions 513b and 514b of the second cable form a second cable couplet coupling the second cable to the movable component, and the distal portions 515b and 516b of the third cable form a third cable couplet coupling the third cable to the movable component.
  • the distal portions 511 b-516b terminate at the wrist 522.
  • the cable couplets may include distal portions corresponding to separate cable segments.
  • the distal portions 511 b-516b wrap around the wrist 522.
  • the cable couplets may include distal portions corresponding to the same cable segment.
  • control system 140 may be configured to generate commands to operate the drive members 501-503 to control the grip, pitch and/or yaw of the movable component.
  • the control system 140 may generate commands to cause the drive members 501 to rotate.
  • the control system 140 may generate commands to cause the drive members 501 and 502 to rotate in a first direction and drive member 503 to rotate in the opposite direction.
  • the control system 140 may generate commands to cause the drive members 502 and 503 to rotate in a first direction.
  • FIG. 6 illustrated is an example computing environment 600 that includes a training server 680 (such as the training server 180) coupled to a control system 640 (such as the control system 140) of computer-assisted system (such as the computer- assisted system 100) via a network 610.
  • a training server 680 such as the training server 180
  • a control system 640 such as the control system 140
  • computer-assisted system such as the computer- assisted system 100
  • FIG. 6 depicts a single server 680
  • the server 680 may be part of a cloud network or may otherwise communicate with other hardware or software components within one or more cloud computing environments to send, retrieve, or otherwise analyze data or information described herein.
  • the server 680 may comprise an on-premise computing environment, a multi-cloud computing environment, a public cloud computing environment, a private cloud computing environment, and/or a hybrid cloud computing environment.
  • an entity e.g., a business
  • may host one or more services in a public cloud computing environment e.g., Facebook Cloud, Amazon Web Services (AWS), Google Cloud, IBM Cloud, Microsoft Azure, etc.
  • the public cloud computing environment may be a traditional off-premise cloud (/.e., not physically hosted at a location owned/controlled by the business).
  • aspects of the public cloud may be hosted on-premise at a location owned/controlled by the business.
  • the public cloud may be partitioned using visualization and multi-tenancy techniques and may include one or more infrastructure-as-a-service (laaS) and/or platform-as-a-service (PaaS) services.
  • laaS infrastructure-as-a-service
  • PaaS platform-as-a-service
  • the memory 685 may include one or more forms of volatile and/or non-volatile, fixed and/or removable memory, such as read-only memory (ROM), electronic programmable read-only memory (EPROM), random access memory (RAM), erasable electronic programmable read-only memory (EEPROM), and/or other hard drives, flash memory, MicroSD cards, and others.
  • the memory 685 may store an operating system (OS) (e.g., Microsoft Windows, Linux, UNIX, etc.) capable of facilitating the functionalities, apps, methods, or other software as described herein.
  • OS operating system
  • a computer program or computer based product, application, or code (e.g., the model(s), such as age determination training models 698, 699) may be stored on a computer usable storage medium, or tangible, non-transitory computer-readable medium (e.g., standard random access memory (RAM), an optical disc, a universal serial bus (USB) drive, or the like) having such computer-readable program code or computer instructions embodied therein, wherein the computer-readable program code or computer instructions may be installed on or otherwise adapted to be executed by the processor(s) 682 (e.g., working in connection with the respective operating system in memory 685) to facilitate, implement, or perform the machine readable instructions, methods, processes, elements or limitations, as illustrated, depicted, or described for the various flowcharts, illustrations, diagrams, figures, and/or other disclosure herein.
  • the processor(s) 682 e.g., working in connection with the respective operating system in memory 685
  • the memory 685 may include one or more databases 687.
  • the database 687 may be a relational database, such as Oracle, DB2, MySQL, a NoSQL based database, such as MongoDB, or another suitable database.
  • the database 687 may store, for example, models associated with procedures performed via the control system 640 (e.g., an ablation procedure, a biopsy, etc.) or operators of the control system 140 (e.g., a surgeon performing the procedure using the control system 140).
  • Such data may include an indication of the procedure or operator, model data indicative of typical operational data associated with the procedure and/or operator, or any other suitable data.
  • the database 687 may store respective sets of experimental data obtained by operating testing instruments (such as the testing instruments 122) to expiration.
  • the database 687 may store the sets of experimental data to create, train, optimize, and/or fine-tune one or more models for estimating an amount of age accumulated by an operating instrument based upon a respective set of operational data.
  • the server 680 maintains the sets of experimental data and the procedure and/or operator model data in separate databases.
  • the memory 685 may include one or more age determination routines or models 688.
  • a model 688, routine, or other element stored in memory may be referred to as receiving an input, producing or storing an output, or executing the routine, the model 688, or other element.
  • the model 688 may, in fact, execute as instructions on the processor 682. Further, those of skill in the art will appreciate that the model 688, routine, or other instructions may be stored in the memory 685 as executable instructions, which are transmitted to the control system 640 for execution by one or more processors thereof.
  • the models 688 may include a trained age determination model 690.
  • the memory 685 may store a plurality of computing modules 695, implemented as respective sets of computer-executable instructions (e.g., one or more source code libraries, training modules, etc.) as described herein.
  • the I/O module 696 may include or implement an operator interface configured to present information to an administrator or operator of the server 680 and/or receive inputs from the administrator and/or operator of the server 680.
  • the I/O module 696 may include I/O components (e.g., ports, capacitive or resistive touch sensitive input panels, keys, buttons, lights, LEDs), which may be directly accessible via, or attached to, server 680 or may be indirectly accessible via or attached to a personal electronic device (not depicted).
  • an administrator or operator may access the server 680 via the personal electronic device to review information, make changes, input training data, initiate training of the age determination models 690, and/or perform other functions (e.g., provide input into how the age determination models 690 are trained).
  • the server 680 may train the age determination model 690 using two different approaches.
  • a first approach referred to herein as a “data driven model” of “data model”
  • the age determination model 690 generates a change in age based on an interpolation of one or more coordinates of a map of parameters corresponding to operational data.
  • a second approach referred to herein as a “mathematical model” or a “math model”
  • the age determination model 690 determines a change in age by inputting the operational data into an equation of a shape that models age accumulation.
  • the computing modules 695 may include a data model training module 698 to train a data driven age determination model and/or a math model training module 699 to train a mathematical age determination model.
  • the server 680 may first preprocess the sets of experimental data to identify one or more contributing parameters that have a statistically significant impact on the age of the testing instruments. For example, the server 680 may isolate the sets of experimental data where a particular operational parameter under test is varied while generally maintaining the values of the other operational parameters. The server 680 may then generate a plot comparing testing instrument lifetime to different values of the operational parameter under test and calculate a cumulative distribution function to derive a p-value associated with the operational parameter under test.
  • the operational parameter under test may be considered a significantly contributing parameter that is modeled by the age determination model 690 (also referred to herein as a “contributing parameter”).
  • a significance threshold e.g. 10%, 5%, 2%, etc.
  • Embodiments described herein describe age determination models 690 in which the contributing parameters are ⁇ pitch, torque, mechanical work ⁇ or ⁇ pitch, torque, velocity ⁇ . It should be appreciated that in other embodiments, different sets of operational parameters may form the contributing parameters modeled by the age determination model 690.
  • FIG. 7 depicts an example map 700 (sometimes also referred to as a “grid”) in a coordinate spaced defined by the contributing parameters.
  • the map 700 includes a dimension that corresponds to each of the contributing parameters (e.g., torque, pitch, and velocity).
  • the data model training module 698 then defines a number of coordinates in the map 700 to use as reference coordinates for interpolation.
  • the data model training module 698 identifies a 3x3x2 grid of reference coordinates. It should be appreciated that in this illustrated example, there are only two coordinates in the velocity dimension due to the velocity operational parameters being less significant than the pitch and torque operational parameters.
  • the data model training module 698 may define a first coordinate to be a minimum value of the contributing parameter in the sets of experimental data, a second coordinate to be a maximum value of the contributing parameter in the set of experimental data, and a third coordinate to be some value in between (e.g., a midpoint, a median value, an average value, etc.).
  • a first coordinate to be a minimum value of the contributing parameter in the sets of experimental data
  • a second coordinate to be a maximum value of the contributing parameter in the set of experimental data
  • a third coordinate to be some value in between (e.g., a midpoint, a median value, an average value, etc.).
  • just the minimum and maximum values may be used.
  • a coordinate representative of a set of operating data obtained from an operating instrument is very likely to be located within the grid.
  • the data model training module 698 then assigns each of the coordinates a variable “y” representative of an amount of age a cable of an operating instrument accumulates when the operational data associated with the corresponding drive member exhibits the torque, pitch, and velocity values represented by the coordinate.
  • the data model training module 698 may then assign the coordinates an initial value for their respective y variable (e.g., 0.1) and perform a regression analysis (described below with respect to FIG. 9) using the sets of experimental data to solve for the values of the y variables.
  • the data model training module 698 may then store the coordinates and their respective values of the y variables as the model data that forms the age determination model 690.
  • control system 640 may then identify a ⁇ torque, pitch, velocity ⁇ set of values in the operational data provided by a drive member of an operating instrument to identify a coordinate 705 in the map 700 (represented as ytine). The control system 640 may then identify which “cube” in the map 700 bounds the coordinate 705. It should be appreciated that although the term “cube” is used, the bounding region may have any appropriate shape based on the particular coordinates defined by the data model training module 698.
  • the coordinate 705 is located in the front left “cube.” Accordingly, the control system 640 may perform an interpolation of the values of the y variables of the eight coordinates that define the bounding “cube.” More particularly, the control system 640 may perform a weighted average of the eight y values where the weights are determined based on the linear distance between the coordinate 705 and the corresponding bounding coordinate of the map 700. The resulting value is the amount of age the control system 640 adds to the current age of the cable coupled to the drive member.
  • FIG. 8 depicts an example shape 800 used to determine the amount of age accumulated by a cable.
  • the illustrated shaped 800 are based on a generalized logistic function. It should be appreciated in other embodiments, if the contributing parameters exhibit a different relationship, alternative shapes and/or equations may be implemented (such as sigmoid shapes, trigonometric shapes, polynomial shapes, exponential shapes, etc.
  • the user of the server 680 is able to specify the function represented by the shape 800.
  • the math model training module 699 analyzes the sets of experimental data to automatically generate a best guess for the shape 800.
  • the shape 800 is smooth and may be less able to account for local variations in age accumulation than the data driven model. On the other hand, it may be faster to calculate the equation than it is to perform the interpolation techniques associated with the data driven model.
  • the math model training module 699 may generate a generic equation based on the function and inserts a plurality of weights (“y” variables) into the function to define the particular features of the shape 800 (e.g., the degree and position at which the shape 800 curves).
  • the math model training module 699 may then assign the y variables an initial value (e.g., 1) and perform a regression analysis (described below with respect to FIG. 9) using the sets of experimental data to solve for the value y variables.
  • the math model training module 699 may store the equation of the shape 800, with the solved values of the y variables, as the model data that forms the age determination model 690.
  • control system 640 may then identify a ⁇ torque, pitch, mechanical work ⁇ set of values in the operational data provided by a drive member of an operating instrument to input into the equation of the shape 800.
  • control system 640 may derive the mechanical work value from an amount of rotation and torque performed by the drive member.
  • the output of the equation of the shape 800 is the amount of age the control system 640 adds to the current age of the cable coupled to the drive member.
  • FIG. 9 depicted is an example process 900 for performing a regression analysis to solve for the values of the y variables in either the map 700 or the equation of the shape 800.
  • the process 900 may be performed by the server 680 as part of the executing the modules 698, 699.
  • the process 900 is an iterative process to derive the best set of values for the y variables based on the sets of experimental data maintained at the database 687 and the initial guess for the y variables.
  • each set of experimental data may include a significant amount of data.
  • the testing instruments generate over 1 ,000 samples of operational data a second. If a typical testing instrument lasts about an hour, the number of samples in each set of experimental data may be too large to perform the regression analysis in a reasonable amount of time. That said, many of the samples have similar and/or identical sets of operational data.
  • the server 680 may instead generate a histogram that bins together the similar sets of operational data together. The server 680 can then reconstruct the amount of age accumulated by the testing instrument by multiplying the outputs of the age determination model by the respective counts in each bin. As a result, the amount of samples used to train the age determination model is reduced thereby enabling the regression process to complete in a timely manner.
  • the server 680 applies the current values of the y variables to the sets of experimental data. More particularly, for each set of experimental data, the server 680 inputs each sample (or bin) into the age determination model and adds the resulting value to generate an overall amount of age accumulated during the experiment. Accordingly, the server 680 may be configured to output a vector indicating the overall amount of accumulated age for each set of experimental data when the current values of the y variables are applied.
  • the server 680 adjusts the values of y variables.
  • the age is normalized to a scale where a value of 100 indicates an instrument has been operated to expiration.
  • the server 680 may adjust the values of the y variables to reduce the difference between the overall amount of ages included in the vector output at block 990 with 100.
  • the server 680 may utilize the mean square error between the output vector from block 990 and a vector of the same length having all values of 100 as a loss function.
  • the server 680 may implement a multiple regression, a multiple linear regression, a nonlinear regression, and/or other types of regression techniques to adjust multiple independent variables (e.g., the y variables) across experiments.
  • the server 680 may be configured to repeat blocks 990, 995 until the server 680 determines the best set of values for the y variables. In some embodiments, the server 680 determines the best set has been derived when the server 680 is unable to adjust the values for the y variables in manner that reduces error in the age determination model. Additionally, or alternatively, the server 680 may segment the sets of experimental data into training sets of experimental data and validation sets of experimental data. In these embodiments, the server 680 may only utilize the training sets of experimental data at block 990. The server 680 may then apply the values for the y variables to the validation sets of experimental data to determine whether the age determination model satisfies a validation metric (e.g., mean square error or other error metric).
  • a validation metric e.g., mean square error or other error metric
  • the server 680 may determine that the best set of values for the y variables has been reached. Regardless, when the server 680 detects the best set of values for the y variables, the server 680 may set the current values of the y variables as the values of the y variables in the output age determination model 690. It should be appreciated that in view of the limitations on collecting sets of experimental data, in some embodiments, the validation sets of experimental data may also be utilized as training sets of experimental data.
  • the server 680 may further utilize the sets of experimental data to derive an age threshold that more reliably indicates the expiration of an instrument than the 100 value used to train the age determination model.
  • the server 680 may plot the overall amount of accumulated age associated with the sets of experimental data.
  • the server 680 may then fit a distribution curve (e.g., a normal distribution curve, a lognormal distribution curve, a Weibull distribution curve, etc.) to the plot.
  • a distribution curve e.g., a normal distribution curve, a lognormal distribution curve, a Weibull distribution curve, etc.
  • the server 680 may identify the age value associated with a threshold value (e.g., 2%, 5%, 10%) of the corresponding cumulative distribution function.
  • a threshold value e.g., 2%, 5%, 10%
  • the server 680 may prevent an operating instrument from unexpectedly expiring in most scenarios.
  • the 5% threshold balances the desire to prevent instruments from unexpectedly expiring with the costs associated with expiring a functional operating instrument early.
  • the server 680 may then update the age determination model 690 such that the value derived from the distribution curve, and not 100, is used as the age when an operating instrument is expired
  • the server 680 may perform the aforementioned actions to generate a separate age determination model 690 for each cable (and/or proximal end thereof) of the instrument. Accordingly, in operation, the control system 640 may input the set of operational data obtained from each drive member into the corresponding age determination model. This enables the age determination models 690 to account for differences in how age is accumulated to each cable to provide a more accurate determination of which cable is the limiting cable and/or provide a more accurate estimation of an amount of life remaining in an operating instrument.
  • the server 680 may perform similar techniques to retrain the age determination model 690 using additional data (e.g., sets of operating data compiled by the control system 640 while performing a procedure).
  • additional data e.g., sets of operating data compiled by the control system 640 while performing a procedure.
  • FIG. 10 depicts a flow diagram of an exemplary computer-implemented method 1000 for generating a model according to an embodiment.
  • the method 1000 may be performed by one or more processors (such as the processors 682) executing instructions stored in one or more computer-readable media (such as the memory 685) of a server (such as the servers 180, 680).
  • processors such as the processors 682
  • computer-readable media such as the memory 685
  • server such as the servers 180, 680
  • the method 1000 may include obtaining one or more sets of experimental data indicative of one or more testing instruments (such as instruments 122, 2400, 3400) being operated to expiration (block 1010), wherein each testing instrument of the one or more testing instruments includes a distal end (such as the distal ends 310, 510), a proximal end (such as the proximal ends 305, 505), a movable component (such as the working portion 126, the movable component 2460, or the wrists 322, 522) at the distal end, an instrument control system (such as the instrument control systems 2700, 3700) at the proximal end, and a plurality of cables (such as the cables 2420, 3420, 3430) connecting the movable component and the instrument control system such that movement of the movable component is controlled by driving the instrument control system.
  • each testing instrument of the one or more testing instruments includes a distal end (such as the distal ends 310, 510), a proximal end (such as the proxi
  • the method 1000 may include generating an age determination model (such as the age determination models 690) based on the one or more sets of experimental data (block 1020), the age determination model configured to provide a change in instrument age of an operating instrument based on one or more sets of operational data associated with the operation of the operating instrument.
  • an age determination model such as the age determination models 690
  • the age determination model configured to provide a change in instrument age of an operating instrument based on one or more sets of operational data associated with the operation of the operating instrument.
  • the instrument age of the operating instrument is based on an age of a limiting cable of the operating instrument, the limiting cable having a highest age value.
  • operational data is associated with the operating instrument and includes sets of operational data associated with each of the plurality of cables
  • inputting the operational data into the age determination model may include inputting each set of operational data to obtain a change in age for each of the plurality of cables.
  • performing the regression analysis comprises: segmenting the one or more sets of experimental data into a training set of experimental data and a validation set of experimental data; and performing the regression analysis using the training set of experimental data.
  • identifying the equation of the shape or one or more contributing parameters is based on user-input or system-prediction.
  • generating the age determination model may include analyzing the one or more sets of experimental data to generate a map (such as the map 700) in a feature space defined by the one or more contributing parameters that associates a coordinate in the feature space with a change in an age to the operating instrument having values of the one or more contributing parameters represented by the coordinate; and generating the age determination model such that the age determination model increases an amount of age associated with the operating instrument by accepting an input coordinate (such as the coordinate 705) indicative of respective values of the one or more contributing parameters and outputting, based on the map, a change in the age to the operating instrument, wherein to output the change in age for the input coordinate, the age determination model interpolates changes in the instrument age from one or more coordinates in the map.
  • the age determination model uses a k-nearest neighbor algorithm to interpolate the changes in the age of the operating instrument from the one or more coordinates in the map.
  • the age determination model applies a linear interpolation algorithm to interpolate the changes in the age of the operating instrument age the one or more coordinates in the map.
  • GUIs 1100A-C indicating the age of an operating instrument at different points in time.
  • the user interfaces 1100A-C may be presented by a display device (such as the display device 112) of a computer-assisted system (such as the computer-assisted system 100).
  • a control system such as the control systems 140, 640
  • the workstation and/or a combination thereof may generate the GUIs 1100A-C and/or the data displayed thereby.
  • the GUIs 1100A-C enable a user to visualize image data generated by an imaging instrument of the computer-assisted system.
  • the image data includes a representation of an operating instrument 1122 (such as an operating instrument 122).
  • the GUIs 1100A-C may also include an age indicator 1120 that indicates the age of the operating instrument 1122 and, in some embodiments, an estimated lifetime remaining for the operating instrument 1122.
  • the control system may highlight and/or otherwise indicate the operating instrument 1122 corresponding to the age indicator 1120.
  • the control system may include a data store (such as the memory 160) to store, for example, one or more age determination models (such the age determination model 690) trained using any one of the methods, algorithms, equations, models and/or techniques described herein, or in any other suitable manner.
  • the memory may store a different model for each cable (and/or proximal end thereof) of the operating instruments.
  • the memory may also store a current age associated with the operating instrument 1122 and/or the cables thereof.
  • the control system obtains operational data associated with the operation of the operating instrument 1122. This may include sets of operational data associated with each of the plurality of cables of the operating instrument 1122 (e.g., the operational data generated by the drive members, such as the drive members 2710, 2720, 3710, 3720, and/or the instrument control systems 2700, 3700).
  • the operational data may include one or more of mechanical work of the drive member associated with a cable, a pitch of the movable component, tension of the cable, a torque associated with the cable, a velocity associated with the cable, an acceleration associated with the cable, an orientation of the movable component, an amount of wear of the cable, or an operational history of the operating instrument 1122.
  • the control system may then identify the portion of the operational data corresponding to the parameters of the age determination models (e.g., the contributing parameters) for input into the respective age determination models. In response, the control system obtains a change in age for each of the plurality of cables. The control system then updates the stored age for each of the cables (and/or proximal ends thereof) by adding the output change in accumulated age. As described herein, the age of the operating instrument 1122 may be based on the age of a limiting cable of the plurality of cables. Accordingly, the control system may identify the cable (and/or proximal end thereof) that is the limiting cable when generating the estimated age and/or the lifetime remaining provided via the age indicator 1120.
  • the age of the operating instrument 1122 may be based on the age of a limiting cable of the plurality of cables. Accordingly, the control system may identify the cable (and/or proximal end thereof) that is the limiting cable when generating the estimated age and/or the lifetime remaining provided via the age indicator 1120.
  • the control system may obtain operator profile data and/or procedure profile data to generate the prediction of remaining usage based on expected future values for the operational data. Additionally or alternatively, the amount of usage remaining may be determined, in part, based on a current or average age accumulation rate during the current procedure.
  • the GUI 1100B includes an alert 1130A configured to warn the operator as to the relatively limited amount of usage remaining for the operating instrument 1122.
  • the control system may also generate an audio alert (e.g., a warning sound), a tactile alert (e.g., vibrating of the instrument), or any other suitable alert.
  • the GUI 1100C includes an alert 1130B configured to warn the operator as to the expiration of the operating instrument 1122.
  • the control system may also generate an audio alert (e.g., a warning sound), a tactile alert (e.g., vibrating of the instrument), or any other suitable alert.
  • the control system may automatically intervene to mitigate the impact of the operating instrument 1122 expiring.
  • the control system may implement a remedial action such as restricting a range of motion of the operating instrument 1122 (e.g., disabling operation of the instrument in a manner that exhibits a threshold amount of a contributing parameter), reducing the torque limit of one or more cables of the operating instrument 1122, providing an interface option to engage an automatic retraction of the operating instrument 1122, preventing usage of a movable device of the operating instrument 1122 (e.g., force-expiring the instruments), or any other suitable manner of limiting of operation of the operating instrument. Any such limiting of operation may also be indicated via a display and/or alert.
  • the control system may include a memory for storing operator preferences associated with the alerts/remedial actions.
  • the operator preferences may indicate an alert threshold (e.g., as defined by a percentage of the overall amount of age) and any automated interventions (e.g., alerts, range of motion limits, etc.) associated therewith. Accordingly, the operator may indicate their alert preferences to be consistent with their preferred level of alerting.
  • the control system may allow the surgeon (e.g., via a user interface of the control system) to expire the instrument, disable some capabilities of the instrument, disregard the alert, or any other suitable course of action.
  • FIGS. 11 A-11C only represent one example technique for indicating an age of the operating instruments to an operator.
  • alternate indicators may be provided additionally and/or instead of the age indicator 1120.
  • the age indicator 1120 may include an indication of age (e.g., as a percentage of current age to the threshold age cutoff) instead of an estimated time remaining.
  • FIG. 12 depicts a flow diagram of an exemplary computer-implemented method 1200 for providing guidance to a user of a computer-assisted system (such as computer- assisted system 100), based on the age of an operating instrument according to an embodiment.
  • the method 1200 may be performed by one or more processors (such as the processor system 150) of a control system (such as the control systems 140, 640).
  • the method 1200 may include storing, in a data store (such as the memory 160) of the control system, an instrument age associated with an operating instrument (such as the instruments 122, 2400, 3400,1122) (block 1210), wherein the operating instrument includes a distal end (such as the distal ends 310, 510), a proximal end (such as the proximal ends (305, 505), a movable component (such as the working portion 126 or the movable component 2460, or the wrists 322, 522) at the distal end, an instrument control system (such as the instrument control systems 2700, 3700) at the proximal end, and a plurality of cables (such as the cables 2420, 3420, 3430) connecting the movable component and the instrument control system such that movement of the movable component is controlled by driving the instrument control system.
  • a data store such as the memory 160
  • an instrument age associated with an operating instrument such as the instruments 122, 2400, 3400,1122
  • the method 1200 may include obtaining operational data associated with the operation of the operating instrument (block 1220).
  • the method 1200 may include obtaining a change in the instrument age associated with the operating instrument by inputting the operational data into an age determination model (such as the age determination models 690) (block 1230).
  • an age determination model such as the age determination models 690
  • the method 1200 may include updating the stored instrument age of the operating instrument based on the obtained change in the instrument age (block 1240).
  • the operational data associated with the operating instrument includes sets of operational data associated with each of the plurality of cables, and inputting the operational data into the age determination model may include inputting each set of operational data to obtain a change in age for each of the plurality of cables.
  • the age of the operating instrument is based on the age of a limiting cable of the plurality of cables, the limiting cable having a highest age value.
  • the operational data includes one or more of mechanical work of the drive member associated with a cable, a pitch of the movable component, tension of the cable, a torque associated with the cable, a velocity associated with the cable, an acceleration associated with the cable, an orientation of the movable component, an amount of wear of the cable, or an operational history of the instrument.
  • control system may further display, via a display device (such as the display device 112), the updated age (such as via the age indicator 1120) of the operating instrument.
  • a display device such as the display device 112
  • the updated age such as via the age indicator 1120
  • control system may further estimate, based on the updated age of the operating instrument, an amount of usage time remaining associated with the operating instrument (such as via the age indicator 1120); and display, via the display device, the estimated amount of usage time remaining.
  • control system may further determine an age accumulation rate at which the age of the operating instrument is accumulating during a current procedure; and determine, based on the age accumulation rate, an amount of usage time remaining for the operating instrument.
  • the control system may further obtain procedure profile data associated with at least one procedure previously performed by one or more operators using the same type of instrument as the operating instrument; determine an expected age accumulation rate based on the procedure profile data; and determine, based on the expected age accumulation rate, an amount of usage time remaining for the operating instrument.
  • control system may further obtain operator profile data associated with at least one procedure previously performed by the operator using the same type of instrument as the operating instrument; determine an expected age accumulation rate based on the operator profile data; and determine, based on the expected age accumulation rate, an amount of usage time remaining for the operating instrument.
  • the remedial action may include displaying, via a display device, an alert (such as the alerts 1130A, 1130B) or limiting operation of the operating instrument.
  • limiting operation of the operating instrument may include restricting a range of motion associated with the movable component of the operating instrument; reducing one or more torque limits of the operating instrument; or preventing usage of the operating instrument.
  • inputting the operational data into the age determination model may include generating a coordinate (such as the coordinate 705) for a map (such as the map 700) having dimensions based on one or more contributing parameters of the age determination model; and obtaining the change in age based upon an interpolation between one or more coordinates in the map corresponding to one or more sets of experimental data generated by operating one or more testing instruments to expiration.
  • inputting the operational data into the age determination model comprises: inputting the operational data into an equation of a shape (such as the equation of the shape 800), wherein the equation of the shape is generated may include identifying, based on the one or more sets experimental data generated by operating one or more testing instruments to expiration, one or more contributing parameters that exhibit a statistical significance on the age of at least one cable of a plurality of cables of a testing instrument beyond a significance threshold; identifying the equation of the shape such that the shape models cable age, wherein the equation of the shape includes input parameters corresponding to the one or more contributing parameters and one or more unknown constant values; and performing a regression analysis (such as via the process 900) of the equation using the one or more sets of experimental data to solve for the unknown constant values.
  • an equation of a shape such as the equation of the shape 800
  • the equation of the shape is generated may include identifying, based on the one or more sets experimental data generated by operating one or more testing instruments to expiration, one or more contributing parameters that exhibit a statistical significance on the age of at least one
  • control system 140 may be implemented in software for execution on one or more processors of a computer system.
  • the software may include code that when executed by the one or more processors, configures the one or more processors to perform various functionalities as discussed herein.
  • the code may be stored in a non-transitory computer readable storage medium (e.g., a memory, magnetic storage, optical storage, solid-state storage, etc.).
  • the computer readable storage medium may be part of a computer readable storage device, such as an electronic circuit, a semiconductor device, a semiconductor memory device, a read only memory (ROM), a flash memory, an erasable programmable read only memory (EPROM); a floppy diskette, a CD-ROM, an optical disk, a hard disk, or other storage device.
  • the code may be downloaded via computer networks such as the Internet, Intranet, etc. for storage on the computer readable storage medium.
  • the code may be executed by any of a wide variety of centralized or distributed data processing architectures.
  • the programmed instructions of the code may be implemented as a number of separate programs or subroutines, or they may be integrated into a number of other aspects of the systems described herein.
  • wireless connections may use wireless communication protocols such as Bluetooth, near-field communication (NFC), Infrared Data Association (IrDA), home radio frequency (HomeRF), IEEE 502.11 , Digital Enhanced Cordless Telecommunications (DECT), and wireless medical telemetry service (WMTS).
  • wireless communication protocols such as Bluetooth, near-field communication (NFC), Infrared Data Association (IrDA), home radio frequency (HomeRF), IEEE 502.11 , Digital Enhanced Cordless Telecommunications (DECT), and wireless medical telemetry service (WMTS).

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  • Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Public Health (AREA)
  • Biomedical Technology (AREA)
  • Medical Informatics (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Surgery (AREA)
  • Epidemiology (AREA)
  • General Business, Economics & Management (AREA)
  • Data Mining & Analysis (AREA)
  • Business, Economics & Management (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Pathology (AREA)
  • Robotics (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Molecular Biology (AREA)
  • Animal Behavior & Ethology (AREA)
  • Veterinary Medicine (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Databases & Information Systems (AREA)
  • Manipulator (AREA)

Abstract

L'invention concerne des systèmes et des procédés permettant de générer un modèle de détermination d'âge sur la base d'ensembles de données expérimentales d'instruments de test. Un système de commande d'un système assisté par ordinateur est configuré pour utiliser le modèle de détermination d'âge pour fournir un changement d'âge d'instrument d'un instrument opérationnel sous sa commande. Le système de commande peut fournir un guidage à un utilisateur sur la base de l'âge de l'instrument opérationnel et peut effectuer une ou plusieurs actions correctives lorsqu'un âge d'instrument mis à jour de l'instrument opérationnel dépasse un seuil d'âge.
PCT/US2024/043127 2023-08-22 2024-08-21 Estimation de l'âge d'instruments chirurgicaux entraînés par câble Pending WO2025042928A1 (fr)

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US202363578142P 2023-08-22 2023-08-22
US63/578,142 2023-08-22

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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20190274769A1 (en) * 2018-03-12 2019-09-12 Ethicon Llc Cable failure detection
US20200363795A1 (en) * 2017-08-16 2020-11-19 Covidien Lp Preventative maintenance of robotic surgical systems
WO2023012574A1 (fr) * 2021-08-03 2023-02-09 Covidien Lp Système et procédé de prédiction d'utilisation d'instrument chirurgical
WO2023022913A1 (fr) * 2021-08-17 2023-02-23 Intuitive Surgical Operations, Inc. Structures de guidage et de commande de câble d'instrument chirurgical

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20200363795A1 (en) * 2017-08-16 2020-11-19 Covidien Lp Preventative maintenance of robotic surgical systems
US20190274769A1 (en) * 2018-03-12 2019-09-12 Ethicon Llc Cable failure detection
WO2023012574A1 (fr) * 2021-08-03 2023-02-09 Covidien Lp Système et procédé de prédiction d'utilisation d'instrument chirurgical
WO2023022913A1 (fr) * 2021-08-17 2023-02-23 Intuitive Surgical Operations, Inc. Structures de guidage et de commande de câble d'instrument chirurgical

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