Data capture and adaptive guidance for robotic surgery with elongate medical devices

Abstract

An exemplary data capture system that generates a profile using captured parameters from a reference operator. The data capture system includes a user interface that receives input from a reference operator for operation of one or more elongated medical devices (EMDs), a sensor system that captures parameters associated with the input from the reference operator, and a processing unit that generates at least one profile using the captured parameters, the profile being associated with characteristics of the reference operator.

Description

[0001] Cross-references to related applications

[0002] This application claims the benefit of U.S. Provisional Application 62 / 874,177, filed July 15, 2019, entitled “DATA CAPTURE AND ADAPTIVE GUIDANCE FOR ROBOTIC PROCEDURES WITH AN ELONGATED MEDICAL DEVICE” (Case No. C130-310). Technical Field

[0003] This invention generally relates to the field of robotic medical surgical systems, and more specifically, to systems, apparatus, and methods related to capturing data associated with user input and providing adaptive guidance for surgeries using slender medical devices. Background Technology

[0004] Catheters and other elongated medical devices (EMDs) are used in minimally invasive medical procedures to diagnose and treat various diseases of the vascular system, including neurovascular interventions (NVI), percutaneous coronary interventions (PCI), and peripheral vascular interventions (PVI), also known as neurointerventional procedures. These procedures typically involve guiding a guidewire through the vascular system and advancing a catheter through the guidewire to deliver treatment. Catheter insertion begins with the use of a guide sheath inserted into the appropriate vessel, such as an artery or vein, using standard percutaneous techniques. Through the guide sheath, the sheath or guiding catheter is then advanced over the diagnostic guidewire to the primary location, such as the internal carotid artery for NVI, the coronary ostium for PCI, or the superficial femoral artery for PVI. A guidewire adapted to the vascular system is then guided through the sheath or guiding catheter to the target location within the vascular system. In some cases, such as in convoluted anatomy, a support catheter or microcatheter is inserted over the guidewire to assist in its guidance. Physicians or operators can use imaging systems (e.g., fluorescein microscopes) to obtain cine images with contrast injections and select a fixed frame as a roadmap to guide the guidewire or catheter to the target location, such as a lesion. Contrast-enhanced images are also obtained as the physician delivers the guidewire or catheter, allowing the physician to verify that the device has moved along the correct path to the target location. When using fluoroscopy to visualize anatomical structures, the physician manipulates the proximal end of the guidewire or catheter to guide the distal end into the appropriate vessel toward the lesion or target anatomical location, avoiding progression into branch vessels.

[0005] Robotic catheter-based surgical systems have been developed to assist physicians in performing catheter insertion procedures such as NVI, PCI, and PVI. Examples of NVI procedures include coil embolization of aneurysms, liquid embolization of arteriovenous malformations, and mechanical thrombectomy for large vessel occlusion in cases of acute ischemic stroke. In NVI procedures, physicians use a robotic system to achieve access to the target lesion by controlling the manipulation of a neurovascular guidewire and a microcatheter to provide treatment and restore normal blood flow. The target access is achieved by a sheath or guide catheter, but intermediate catheters may also be needed for more distal areas or to provide adequate support for the microcatheter and guidewire. Depending on the type of lesion and the treatment, the distal end of the guidewire is guided into or across the lesion. To treat an aneurysm, the microcatheter is advanced into the lesion and the guidewire is removed, and several embolization coils are deployed through the microcatheter into the aneurysm to stop blood flow into it. To treat an arteriovenous malformation, a liquid embolic agent is injected into the malformation site through the microcatheter. Mechanical thrombectomy can be performed to treat vascular occlusion by aspiration and / or the use of a stent retriever. Depending on the location of the clot, aspiration can be performed via an aspiration catheter or, for smaller arteries, via a microcatheter. Once the aspiration catheter is at the lesion site, negative pressure is applied to remove the clot through the catheter. Alternatively, the clot can be removed by deploying a stent retriever via a microcatheter. Once the clot has adhered to the stent retriever, it is retrieved by retracting the stent retriever and the microcatheter (or intermediate catheter) into the guiding catheter.

[0006] In PCI, physicians use robotic systems to achieve access to the lesion by manipulating a guidewire in the coronary artery to provide treatment and restore normal blood flow. This access is achieved by placing a guiding catheter in the ostium of the coronary artery. The distal end of the guidewire is guided through the lesion, and for complex anatomy, a microcatheter can be used to provide adequate support for the guidewire. Blood flow is restored by delivering and deploying a stent or balloon at the lesion. The lesion may require preparation before stent implantation, either by delivering a balloon for pre-dilation of the lesion or by performing plaque resection using a balloon on a guidewire, such as a laser or rotational atherectomy catheter. Diagnostic imaging and physiological measurements can be performed using imaging catheters or fractional flow reserve (FFR) measurements to determine the appropriate treatment.

[0007] In PVI, physicians use robotic systems to deliver treatment and restore blood flow using techniques similar to NVI. The distal tip of a guidewire is guided through the lesion, and microcatheters can be used to provide adequate support for the guidewire in complex anatomical structures. Blood flow is restored by delivering and deploying a stent or balloon to the lesion. As with PCI, lesion preparation and diagnostic imaging are also available.

[0008] When distal support of the catheter or guidewire is required for purposes such as guiding a tortuous or calcified vascular system, reaching a distal anatomical location, or traversing a hard lesion, an on-wire (OTW) catheter or coaxial system is used. An OTW catheter has an inner lumen for a guidewire that extends the entire length of the catheter. This provides a relatively stable system because the guidewire is supported along its entire length. However, compared to quick-change catheters (see below), this system has some disadvantages, including higher friction and a longer overall length. Typically, to remove or change the OTW catheter while maintaining the position of the indwelling guidewire, the exposed length of the guidewire (outside the patient) must be longer than the OTW catheter. A 300 cm guidewire is usually sufficient for this purpose and is often referred to as a change-length guidewire. Due to the length of the guidewire, two operators are required to remove or change the OTW catheter. This becomes even more challenging if a triple coaxial system (also known as a quadruple coaxial catheter) is used, which is referred to in the art as a triaxial system. However, due to its stability, the OTW system is frequently used in NVI and PVI procedures. On the other hand, PCI procedures typically use quick-change (or single-rail) catheters. In a quick-change catheter, the guidewire lumen only extends through the distal segment of the catheter, known as the single-rail or quick-change (RX) segment. Using the RX system, the operator manipulates the interventional devices parallel to each other (unlike the OTW system, where devices are manipulated in a serial configuration), and the exposed length of the guidewire only needs to be slightly longer than the RX segment of the catheter. Quick-change guidewires are typically 180–200 cm long. Given the shorter guidewire and single-rail design, RX catheters can be changed by a single operator. However, RX catheters are often insufficient when more distal support is required. Summary of the Invention

[0009] According to an embodiment, a data capture system generates profiles using capture parameters from a reference operator. The data capture system includes: a user interface that receives input from a reference operator for operation of one or more elongated medical devices (EMDs); a sensor system that captures parameters associated with the input from the reference operator; and a processing unit that uses the capture parameters to generate at least one profile associated with characteristics of the reference operator.

[0010] In one example, the parameters detected by the sensor include at least one of motion parameters or load parameters.

[0011] In one example, the motion parameters and the load parameters include at least one of displacement, linear velocity, linear force, rotational speed, rotational torque, acceleration, or frequency.

[0012] In one example, the parameters detected by the sensor include at least one of the following: (a) a combination of linear velocity and linear force load; (b) a combination of rotational velocity and rotational torque; (c) a combination of displacement and / or velocity and / or acceleration with linear force; or (d) a combination of angular displacement and / or angular velocity and / or angular acceleration with torque.

[0013] In one example, the parameters detected by the sensor include the manipulation frequency of the EMD.

[0014] In one example, the parameters detected by the sensor include two or more combinations of motion parameters, load parameters, position, displacement, frequency, linear velocity, linear force, rotational speed, or rotational torque.

[0015] In one example, the data capture system is either a standalone system or part of another system, such as a robotic medical system or a training system.

[0016] In one example, the sensor system includes contact and / or non-contact sensors to detect the movement and / or load of an EMD or a stack of EMDs.

[0017] In one example, the sensor system includes signal conditioning.

[0018] In one example, the user interface includes more than one EMD, and the sensor system detects input parameters for concurrent operation of more than one EMD.

[0019] In one example, the input parameters are captured based on a heuristic model.

[0020] In one example, the characteristics of the reference operator include at least one of the doctor's metadata.

[0021] In one example, at least a portion of the captured data may be associated with case metadata.

[0022] In one example, at least a portion of the captured data may be a combination of doctor metadata and case metadata.

[0023] In one example, the recording and retrieval of data can be local or non-local for the system.

[0024] In one example, the processing unit utilizes algorithmic analysis of inputs from one or more operators when creating a file.

[0025] In one example, the processing unit will generate a power profile associated with an operator profile containing motion and load parameters.

[0026] In one example, the processing unit calculates and determines the envelope of the range of motion, load, and power parameters.

[0027] In one example, the processing unit will generate adaptive guidance parameters for EMD manipulation based on motion and load parameters contained in the operator's profile.

[0028] In one example, the processing unit generates motion profiles and / or load profiles associated with one or more EMDs.

[0029] In one example, the motion profile is constructed solely based on motion parameters from an operator profile for an EMD, including simultaneous rotational and linear motions of the EMD.

[0030] In one example, the motion profile is constructed based on motion parameters for operator profiles of more than one EMD, including simultaneous rotational and / or linear motion of a first EMD and rotational and / or linear motion of a second EMD.

[0031] In one example, the motion profile is constructed based on load parameters for operator profiles for more than one EMD.

[0032] In one example, the motion profile is constructed based on both motion and load parameters of the operator profile for more than one EMD.

[0033] In one example, the processing unit generates a master profile by combining physician metadata and case metadata.

[0034] In one example, the processing unit combines the captured data from the reference operator with additional captured data from the additional operator to generate an aggregated archive.

[0035] In one example, the generated archive is updated with additional captured data from another additional operator.

[0036] In one example, the processing unit updates the file when new input data becomes available, for example, after a series of ongoing surgeries.

[0037] In one example, the processing unit transforms input from the operator, combined with other metadata, into operation control equations, operation constraints, and commands.

[0038] In one example, the processing unit is capable of generating or updating the archives and converting data into operational rules offline or in real time.

[0039] In one example, the processing unit provides feedback to a second operator based on the generated file.

[0040] In one example, the feedback is provided during the training simulation.

[0041] In one example, the feedback is provided during the on-site surgery performed by the second operator.

[0042] In one example, the second operator is able to selectively accept or reject the feedback.

[0043] In one example, the processing unit generates adaptive boot parameters.

[0044] In one example, the adaptive guidance parameters include at least one of the following: operational control equations or constraints applied to the EMD or surgery, surgical recommendations, motion profiles, or motion and load based on general rules.

[0045] In another embodiment, a robotic medical system includes: a module that independently and collaboratively actuates one or more EMDs; a user interface that receives input from a reference operator to manipulate the EMDs; a sensor system for detecting motion and / or load parameters applied to the EMDs; a data acquisition section that captures parameters detected by the sensors and associated with the input from the reference operator, the captured parameters including at least one motion or load parameter, wherein the data acquisition section correlates the captured parameters with characteristics of the reference operator; and a processing unit that converts the detected parameters into operational control equations for the elongated medical device and the procedure.

[0046] In another embodiment, a method includes: capturing input parameters from a reference operator of a robotic device, the captured input parameters including at least one motion or load parameter; converting the captured input parameters into operating commands for the robotic device; and using the captured input parameters to generate a profile associated with characteristics of the reference operator.

[0047] In another embodiment, a non-transitory computer-readable storage medium is encoded with instructions executable by a processor of a computing system. The computer-readable storage medium includes instructions for: capturing input parameters from a reference operator of a robotic device, the captured input parameters including at least one motion or load parameter; converting the captured input parameters into operating commands for the robotic device; and using the captured input parameters to generate a profile associated with characteristics of the reference operator.

[0048] In another embodiment, a computer-implemented method includes: capturing input parameters from a reference operator of a robotic device, the captured input parameters including at least one motion or load parameter; converting the captured input parameters into operating commands for the robotic device; and using the captured input parameters to generate a profile associated with characteristics of the reference operator.

[0049] In another embodiment, a data capture system includes: a user interface that receives input from a reference operator for operation of an elongated medical device, the user interface including sensors to detect parameters associated with the input from the reference operator; a recording portion that captures the parameters detected by the sensors and associated with the input from the reference operator, the captured parameters including at least one motion or load parameter; and a processing unit that generates adaptive guidance parameters for operation of the elongated medical device based on the captured input parameters.

[0050] In another embodiment, a robotic medical system includes: a user interface that receives input from a reference operator; a sensor system that detects parameters associated with the input from the reference operator; a data acquisition section that captures the parameters detected by the sensors and associated with the input from the reference operator; a processing unit that converts the input from the operator into adaptive guidance for operation of an elongated medical device and surgery; and at least one module that independently and cooperatively actuates one or more EMDs.

[0051] In another embodiment, a method includes: capturing input parameters from a reference operator of an elongated medical device, the captured input parameters including at least one motion or load parameter; converting the captured input parameters into operating commands for the elongated medical device; and generating guidance parameters for the elongated medical device based on the captured input parameters.

[0052] In another embodiment, a non-transitory computer-readable storage medium is encoded with instructions executable by a processor of a computing system. The computer-readable storage medium includes instructions for: capturing input parameters from a reference operator of a robotic device, the captured input parameters including at least one motion or load parameter; converting the captured input parameters into operating commands for the robotic device; and generating guidance parameters for the elongated medical device based on the captured input parameters.

[0053] In another embodiment, a computer-implemented method includes: capturing input parameters from a reference operator of a robotic device, the captured input parameters including at least one motion or load parameter; converting the captured input parameters into operating commands for the robotic device; and generating guidance parameters for the elongated medical device based on the captured input parameters.

[0054] In another embodiment, a data capture system for generating a profile using capture parameters from a reference operator includes: a user interface that receives input from a reference operator for operation of one or more elongated medical devices (EMDs); and a sensor system that captures parameters associated with the input from the reference operator, wherein the parameters detected by the sensors include at least one of: (a) a combination of linear velocity and linear force load; (b) a combination of rotational velocity and rotational torque; (c) a combination of displacement and / or velocity and / or acceleration with linear force; or (d) a combination of angular displacement and / or angular velocity and / or angular acceleration with torque.

[0055] In another embodiment, a data capture system for generating a profile using capture parameters from a reference operator includes: a user interface that receives input from a reference operator for operation of one or more elongated medical devices (EMDs); and a sensor system that captures parameters associated with the input from the reference operator, wherein the parameters detected by the sensors include combinations of two or more of motion parameters, load parameters, position, displacement, frequency, linear velocity, linear force, rotational speed, or rotational torque. Attached Figure Description

[0056] The invention will be more fully understood from the following detailed description, taken in conjunction with the accompanying drawings, wherein reference numerals refer to the same parts, and wherein:

[0057] Figure 1 This is a perspective view of an exemplary catheter-based surgical system according to an embodiment;

[0058] Figure 2 This is a schematic block diagram of an exemplary catheter-based surgical system according to an embodiment;

[0059] Figure 3 This is a perspective view of a robot actuator for a catheter-based surgical system according to an embodiment;

[0060] Figure 4 This is a schematic diagram of an exemplary data capture system according to an embodiment for use with a robotic medical system having an elongated medical device (EMD);

[0061] Figure 5This is a schematic diagram of an exemplary robotic medical system with an exemplary data capture system according to an embodiment;

[0062] Figure 6 It is a flowchart illustrating an exemplary method, according to an embodiment, for generating a file associated with operator characteristics using operator input;

[0063] Figure 7 It is a flowchart illustrating an exemplary method for generating adaptive guidance parameters using operator input, according to an embodiment;

[0064] Figure 8 The illustration shows an exemplary data input arrangement and data utilization of a robotic medical system with an EMD according to an embodiment;

[0065] Figure 9 The illustration shows an exemplary actuator / sensor arrangement structure for use with various EMDs according to an embodiment;

[0066] Figure 10 The illustration shows an exemplary data capture linear module for use with various EMDs, according to an embodiment; and

[0067] Figure 11 An exemplary data capture rotation module for use with various EMDs is illustrated according to an embodiment. Detailed Implementation

[0068] Figure 1 This is a perspective view of an exemplary catheter-based surgical system 10 according to an embodiment. The catheter-based surgical system 10 can be used to perform catheter-based medical procedures, such as percutaneous interventional procedures, such as percutaneous coronary intervention (PCI) (e.g., for STEMI treatment), neurovascular interventional procedures (NVI) (e.g., for emergency large vessel occlusion (ELVO)), peripheral vascular interventional procedures (PVI) (e.g., for severe limb ischemia (CLI), etc.). Catheter-based medical procedures may include diagnostic catheterization, during which one or more catheters or other elongated medical devices (EMDs) are used to aid in the diagnosis of a patient's condition. For example, during one embodiment of a catheter-based diagnostic procedure, a contrast agent is injected through a catheter onto one or more arteries, and images of the patient's vascular system are taken. Catheter-based medical procedures may also include catheter-based therapeutic procedures (e.g., angioplasty, stent placement, treatment of peripheral vascular disease, clot removal, treatment of arteriovenous malformations, treatment of aneurysms, etc.), during which a catheter (or other EMD) is used to treat the condition. It can be achieved through auxiliary devices including intravascular ultrasound (IVUS), optical coherence tomography (OCT), fractional flow reserve (FFR) 54 ( Figure 2(As shown in the diagram) to enhance the treatment procedure. However, it should be noted that those skilled in the art will recognize that certain specific percutaneous interventional devices or components (e.g., the type of guidewire, the type of catheter, etc.) can be selected based on the type of procedure to be performed. The catheter-based surgical system 10 can perform any number of catheter-based medical procedures with minor adjustments to accommodate the specific percutaneous interventional device to be used in the procedure.

[0069] The catheter-based surgical system 10 includes a bedside unit 20, a control station 26, and other components. The bedside unit 20 includes a robot actuator 24 and a positioning system 22 positioned adjacent to the patient 12. The patient 12 is supported on a patient table 18. The positioning system 22 is used to position and support the robot actuator 24. The positioning system 22 may be, for example, a robotic arm, an articulated arm, a retainer, etc. The positioning system 22 may be attached at one end to, for example, a track, base, or trolley on the patient table 18. The other end of the positioning system 22 is attached to the robot actuator 24. The positioning system 22 can be removed (along with the robot actuator 24) to allow the patient 12 to be placed on the patient table 18. Once the patient 12 is positioned on the patient table 18, the positioning system 22 can be used to position or position the robot actuator 24 relative to the patient 12 for surgical procedures. In one embodiment, the patient table 18 is operatively supported by a support 17 fixed to the floor and / or ground. The patient table 18 is capable of movement relative to the support 17 in multiple degrees of freedom, such as tilting, pitching, and yawing. Bedside unit 20 may also include a control device and a display 46. Figure 2 (As shown in the diagram). For example, the control unit and display may be located on the housing of the robot driver 24.

[0070] Typically, the robot actuator 24 may be equipped with appropriate percutaneous intervention devices and accessories 48. Figure 2 (as shown herein) (e.g., guidewires, various types of catheters including balloon catheters, stent delivery systems, stent retrievers, embolization coils, liquid embolizing agents, aspiration pumps, devices for delivering contrast agents, medications, hemostatic valve adapters, syringes, stopcock valves, inflation devices, etc.) to allow a user or operator 11 to perform catheter-based medical procedures via a robotic system by operating various control devices, such as those located at control station 26 and inputting them. The bedside unit 20, and in particular the robot actuator 24, may include any number and / or combination of components to provide the functionality described herein to the bedside unit 20. The user or operator 11 at control station 26 is referred to as the control station user or control station operator, and is referred to herein as the user or operator. The user or operator at bedside unit 20 is referred to as the bedside unit user or bedside unit operator. The robot actuator 24 includes components mounted to a track or linear member 60 ( Figure 3Multiple device modules 32a-d (shown in the diagram). A track or linear member 60 guides and supports the device modules. Each device module 32a-d can be used to drive an EMD, such as a catheter or guidewire. For example, a robotic actuator 24 can be used to automatically deliver a guidewire into a diagnostic catheter and into a guiding catheter in an artery of patient 12. One or more devices, such as EMDs, enter the body (e.g., a blood vessel) of patient 12 at insertion point 16 via, for example, a guide sheath.

[0071] Bedside unit 20 communicates with control station 26, allowing signals generated by user input from control station 26 to be transmitted wirelessly or via hardwired to bedside unit 20 to control various functions of bedside unit 20. As described below, control station 26 may include control computing system 34. Figure 2 (as shown in the diagram) or coupled to the bedside unit 20 via the control computing system 34. The bedside unit 20 can also communicate with the control station 26, the control computing system 34 (as shown in the diagram), or via the control computing system 34. Figure 2 Feedback signals (e.g., load, speed, operating status, warning signals, error codes, etc.) are provided by either the control computing system 34 or both. Communication between the various components of the catheter-based surgical system 10 can be provided via a communication link, which can be a wireless connection, a cable connection, or any other means that allows communication between components. The control station 26 or other similar control system can be located at a local location (e.g., Figure 2 The local control station 38 shown is located at a local location or a remote location (e.g., Figure 2 The catheterization system 10 can be operated via a control station at a local location, a control station at a remote location, or both simultaneously. At the local location, the user or operator 11 and the control station 26 are located in the same room or adjacent to the patient 12 and the bedside unit 20. As used herein, the local location is the location of the bedside unit 20 and the patient 12 or object (e.g., animal or carcass), and the remote location is the location of the user or operator 11 and the control station 26 for remotely controlling the bedside unit 20. For example, the control station 26 (and control computing system) at the remote location and the control computing system at the bedside unit 20 and / or the local location can be accessed via the Internet using communication systems and services 36. Figure 2 (as shown in the diagram) to communicate. In one embodiment, the remote location and the local (patient) location are geographically distant from each other, for example, in different rooms in the same building, in different buildings in the same city, in different cities, or in other different locations of the bedside unit 20 and / or patient 12 at the local location where the remote location cannot physically access them.

[0072] Control station 26 typically includes one or more input modules 28 configured to receive user input to operate various components or systems of the catheter-based surgical system 10. In the illustrated embodiment, control station 26 allows a user or operator 11 to control bedside unit 20 to perform catheter-based medical procedures. For example, input modules 28 may be configured to enable bedside unit 20 to perform various tasks using a percutaneous interventional device (e.g., an EMD) interfaced with robot actuator 24 (e.g., to advance, retract, or rotate guidewires, advance, retract, or rotate catheters, inflate or deflate balloons on catheters, position and / or deploy stents, position and / or deploy stent retrieval devices, position and / or deploy coils, inject contrast agents into catheters, inject liquid embolic agents into catheters, inject drugs or saline into catheters, aspirate from catheters, or perform any other function that may be performed as part of a catheter-based medical procedure). Robot actuator 24 includes various actuation mechanisms to cause movement (e.g., axial and rotational movement) of components of bedside unit 20 including percutaneous interventional devices.

[0073] In one embodiment, input module 28 may include one or more touchscreens, joysticks, scroll wheels, and / or buttons. In addition to input module 28, control station 26 may use additional user control devices 44. Figure 2(As shown in the diagram), such as a foot switch and a microphone for voice commands. Input module 28 can be configured to advance, retract, or rotate various components and percutaneous interventional devices, such as guidewires, and one or more catheters or microcatheters. For example, buttons may include an emergency stop button, a multiplier button, a device selection button, and an auto-movement button. When the emergency stop button is pressed, power (e.g., electrical power) supplied to bedside unit 20 is turned off or removed. In speed control mode, the multiplier button is used to increase or decrease the speed at which the relevant components move in response to manipulation of input module 28. In position control mode, the multiplier button changes the mapping between input distance and output command distance. The device selection button allows the user or operator 11 to select which percutaneous interventional devices loaded into robot actuator 24 are controlled by input module 28. The auto-movement button enables algorithmic movement of catheter-based surgical system 10 on percutaneous interventional devices without direct commands from user or operator 11. In one embodiment, input module 28 may include one or more controls or icons (not shown) displayed on a touchscreen (which may or may not be part of display 30), which, when activated, cause operation of components of the catheter-based surgical system 10. Input module 28 may also include balloon or stent controls configured to inflate or deflate a balloon and / or deploy a stent. Each input module 28 may include one or more buttons, scroll wheels, joysticks, touchscreens, etc., which can be used to control one or more specific components dedicated to that control device. Furthermore, one or more touchscreens may display one or more icons (not shown) associated with various parts of input module 28 or with various components of catheter-based surgical system 10.

[0074] Control station 26 may include display 30. In other embodiments, control station 26 may include two or more displays 30. Display 30 may be configured to display information or patient-specific data to a user or operator 11 located at control station 26. For example, display 30 may be configured to display image data (e.g., X-ray images, MRI images, CT images, ultrasound images, etc.), hemodynamic data (e.g., blood pressure, heart rate, etc.), patient record information (e.g., medical history, age, weight, etc.), lesion or treatment assessment data (e.g., IVUS, OCT, FFR, etc.). Furthermore, display 30 may be configured to display surgery-specific information (e.g., surgical checklist, recommendations, surgery duration, catheter or guidewire position, amount of delivered medication or contrast agent, etc.). Additionally, display 30 may be configured to display information to provide control computing system 34 ( Figure 2 (As shown in the diagram) Related functions. Display 30 may include touchscreen capability to provide some user input capabilities for the system.

[0075] The catheter-based surgical system 10 also includes an imaging system 14. The imaging system 14 can be any medical imaging system (e.g., non-digital X-ray, digital X-ray, CT, MRI, ultrasound, etc.) that can be used in conjunction with catheter-based medical procedures. In an exemplary embodiment, the imaging system 14 is a digital X-ray imaging device that communicates with a control station 26. In one embodiment, the imaging system 14 may include a C-arm ( Figure 1 As shown in the diagram, the C-arm allows the imaging system 14 to rotate partially or completely around the patient 12 to obtain images at different angular positions relative to the patient 12 (e.g., sagittal view, tail view, front and back view, etc.). In one embodiment, the imaging system 14 is a fluorescence fluoroscopy system that includes a C-arm with an X-ray source 13 and a detector 15, also referred to as an image intensifier.

[0076] Imaging system 14 can be configured to capture X-ray images of appropriate areas of the patient 12 during surgery. For example, imaging system 14 can be configured to capture one or more X-ray images of the head to diagnose neurovascular conditions. Imaging system 14 can also be configured to capture one or more X-ray images (e.g., real-time images) during catheter-based medical procedures to help the user or operator 11 of control station 26 properly position guidewires, guiding catheters, microcatheters, stent retrieval devices, coils, stents, balloons, etc., during surgery. These one or more images can be displayed on display 30. For example, images can be displayed on display 30 to allow the user or operator 11 to accurately move the guiding catheter or guidewire to the appropriate position.

[0077] To define orientation, a Cartesian coordinate system with X, Y, and Z axes is introduced. The positive X-axis is oriented along the longitudinal (axial) direction, i.e., from the proximal end to the distal end; in other words, from the proximal side to the distal side. The Y and Z axes lie in a transverse plane relative to the X-axis, with the positive Z-axis pointing upwards, i.e., in the direction opposite to gravity, and the Y-axis is automatically determined by the right-hand rule.

[0078] Figure 2 This is a block diagram of a catheter-based surgical system 10 according to an exemplary embodiment. The catheter-based surgical system 10 may include a control computing system 34. For example, the control computing system 34 may physically be a control station 26 ( Figure 1(As shown in the diagram). The control computing system 34 can typically be an electronic control unit adapted to provide the various functions described herein for the catheter-based surgical system 10. For example, the control computing system 34 can be an embedded system, a dedicated circuit, a general-purpose system programmed with the functions described herein, etc. The control computing system 34 communicates with the bedside unit 20, communication systems and services 36 (e.g., the Internet, firewall, cloud services, session manager, hospital network, etc.), local control station 38, additional communication systems 40 (e.g., telepresence system), remote control station and computing system 42, and patient sensors 56 (e.g., electrocardiogram (ECG) device, electroencephalogram (EEG) device, blood pressure monitor, body temperature monitor, heart rate monitor, respiratory monitor, etc.). The control computing system also communicates with the imaging system 14, patient table 18, additional medical systems 50, contrast agent injection system 52, and auxiliary devices 54 (e.g., IVUS, OCT, FFR, etc.). The bedside unit 20 includes a robot actuator 24, a positioning system 22, and may include additional controls and a display 46. As described above, additional control devices and displays may be located on the housing of the robot actuator 24. Interventional devices and accessories 48 (e.g., guidewires, catheters, etc.) interface with the bedside system 20. In one embodiment, interventional devices and accessories 48 may include dedicated devices (e.g., IVUS catheters, OCT catheters, FFR lines, diagnostic catheters for angiography, etc.) that interface with their respective accessories 54, i.e., IVUS systems, OCT systems, and FFR systems.

[0079] In various embodiments, the control computing system 34 is configured based on the user and input module 28 (e.g., control station 26). Figure 1The interaction with input modules (such as those of local control station 38 or remote control station 42) and / or the generation of control signals based on information accessible to the control computing system 34 enable the use of the catheter-based surgical system 10 to perform medical procedures. Local control station 38 includes one or more displays 30, one or more input modules 28, and an additional user control device 44. The remote control station and computing system 42 may include components similar to those of local control station 38. Remote control station 42 and local control station 38 may be different and may be customized based on their required functionality. The additional user control device 44 may, for example, include one or more foot input controls. Foot input controls may be configured to allow a user to select functions of the imaging system 14, such as turning X-rays on and off and scrolling through different stored images. In another embodiment, foot input devices may be configured to allow a user to select which devices are mapped to a scroll wheel included in input module 28. Additional communication systems 40 (e.g., audio conferencing, video conferencing, telepresence, etc.) can be used to help operators interact with patients, medical staff (e.g., angio-suite staff) and / or bedside devices.

[0080] The catheter-based surgical system 10 may be connected to or configured to include any other systems and / or devices not explicitly shown. For example, the catheter-based surgical system 10 may include an image processing engine, a data storage and archiving system, an automated balloon and / or stent inflation system, a drug injection system, a drug tracking and / or recording system, a user log, an encryption system, a system for restricting access to or use of the catheter-based surgical system 10, etc.

[0081] As mentioned, the control computing system 34 communicates with the bedside unit 20, which includes a robot actuator 24, a positioning system 22, and may include additional control devices and a display 46. The control system 34 can provide control signals to the bedside unit 20 to control the operation of motors and drive mechanisms used to drive percutaneous interventional devices (e.g., guidewires, catheters, etc.). Various drive mechanisms may be provided as part of the robot actuator 24. Figure 3 This is a perspective view of a robot actuator for a catheter-based surgical system 10 according to an embodiment. Figure 3In this embodiment, the robot actuator 24 includes a plurality of device modules 32a-d coupled to a linear member 60. Each device module 32a-d is coupled to the linear member 60 via a stage 62a-d movably mounted to the linear member 60. The device modules 32a-d can be connected to the stages 62a-d using connectors such as bias brackets 78a-d. In another embodiment, the device modules 32a-d are directly mounted to the stages 62a-d. Each stage 62a-d can be independently actuated to move linearly along the linear member 60. Therefore, each stage 62a-d (and its corresponding device module 32a-d coupled to it) can move independently relative to each other and to the linear member 60. A drive mechanism is used to actuate each stage 62a-d. Figure 3 In the illustrated embodiment, the drive mechanism includes an independent stage translation motor 64a-d coupled to each stage 62a-d and a platform drive mechanism 76, such as a lead screw via a rotating nut, a rack via a pinion, a belt via a pinion or pulley, a chain via a sprocket, or the stage translation motor 64a-d itself may be a linear motor. In some embodiments, the stage drive mechanism 76 may be a combination of these mechanisms; for example, each stage 62a-d may employ a different type of stage drive mechanism. In embodiments where the stage drive mechanism is a lead screw and a rotating nut, the lead screw can be rotated and each stage 62a-d can engage and disengage with the lead screw to move, e.g., forward or retract. Figure 3 In the embodiment shown, stations 62a-d and device modules 32a-d are in a serial drive configuration.

[0082] Each device module 32a-d includes a drive module 68a-d and a housing 66a-d mounted on and coupled to the drive module 68a-d. Figure 3In the illustrated embodiment, each housing 66a-d is mounted vertically to the drive module 68a-d. In other embodiments, each housing 66a-d may be mounted to the drive module 68a-d in other orientations. Each housing 66a-d is configured to interface with and support a proximal portion of the EMD (not shown). Furthermore, each housing 66a-d may include elements that provide one or more degrees of freedom in addition to linear motion provided by actuation of the corresponding stage 62a-d for linear movement along the linear member 60. For example, housing 66a-d may include elements that can be used to rotate the EMD when the housing is coupled to the drive module 68a-d. Each drive module 68a-d includes at least one coupler to provide a drive interface for the mechanism in each housing 66a-d to provide additional degrees of freedom. Each housing 66a-d also includes a channel in which device supports 79a-d are located, and each device support 79a-d is used to prevent buckling of the EMD. Support arms 77a, 77b, and 77c are respectively attached to each device module 32a, 32b, and 32c to provide anchor points for supporting the proximal ends of device supports 79b, 79c, and 79d. The robot actuator 24 may also include a device support connector 72 connected to the device support 79, the distal support arm 70, and the support arm 770. The support arm 770 provides anchor points for supporting the proximal end of the distal device support 79a housed in the distal device module 32a. Furthermore, a guide interface support (redirector) 74 may be connected to the device support connector 72 and an EMD (e.g., a guide sheath). This configuration of the robot actuator 24 has the advantage of reducing the size and weight of the robot actuator 24 by using an actuator on a single linear member.

[0083] To prevent pathogen contamination of patients, medical staff are in the bedside unit 20 and patient 12 or subject ( Figure 1 Aseptic techniques are used in the room shown. The room housing the bedside unit 20 and the patient 12 may be, for example, a catheterization lab or vascularization lab. Aseptic techniques include the use of sterile barriers, sterile equipment, appropriate patient preparation, environmental control, and contact guidance. Therefore, all EMDs and interventional accessories are sterilized and can only come into contact with sterile barriers or sterile equipment. In one embodiment, a sterile drape (not shown) is placed on a non-sterile robotic actuator 24. Each cartridge 66a-d is sterilized and serves as a sterilization interface between the drape-covered robotic actuator 24 and at least one EMD. Each cartridge 66a-d may be designed to be sterilized for single use, or to be re-sterilized wholly or partially, such that cartridge 66a-d or its components may be used in multiple procedures.

[0084] In one example, various types of data can be captured during an operation performed by an operator and used to generate profiles associated with various characteristics. These data types are linked to inputs from the operator, which can be received via a user interface and captured by a sensor system. The captured data can be used to generate one or more profiles, which can then be used to facilitate the operation of the robotic medical system by the same or different operators.

[0085] In another example, the captured data can be used to provide adaptive guidance by the same or different operators during training, simulation, or live surgery. As illustrated in the various examples below, guidance parameters may include limitations on the operation of the robotic medical system or other guidance methods.

[0086] definition

[0087] In various examples, the sensor system captures operator input in the form of waveforms (in the time domain), commands, signals, and settings. This data is then processed by the processing unit 124. Figure 4 The data is processed and various mappings and transformations, such as filters, Fourier transforms, and other mathematical or numerical mappings and transformations, are applied to make them operationally usable. When the data capture system is part of a robotic medical system, motion parameters, load parameters, motion and load profiles and limitations, successful and unsuccessful attempts (e.g., the number of attempts to select a branch), total travel for each EMD, and other such parameters are examples captured during a case or data capture event. Furthermore, additional data regarding operator characteristics and the procedure (case) can be used to better represent, describe, classify, or segment the data. The latter is often referred to as metadata.

[0088] In various examples, a profile may include a collection of data associated with a user or group of users. This data may be a collection of metadata, collected kinematic or dynamic (or motion or load) parameters, or parameters derived from algorithms that process metadata and kinematic or dynamic parameters. Kinematic parameters are mathematical representations of a point, body, or volume motion system, such as displacement, velocity, acceleration, time, and frequency (frequency = 1 / time), and trajectory. This does not take into account the load required by the moving device. Dynamic parameters are mathematical representations of a point, body, or volume motion system, such as displacement, velocity, acceleration, time, and frequency (frequency = 1 / time), and trajectory, taking into account the load required by the moving device and the external loads (or losses) experienced by the device or manipulator of the moving device. A profile related to a robot EMD drive system may include relevant force zones (typical, high, maximum), which are further categorized according to the type of surgery, the type of device being driven, the device location within the anatomical structure, velocity thresholds or limits, load thresholds or limits, power thresholds or limits, or the typical device used (device length).

[0089] In some examples, operator-related data, known as physician metadata, is also captured by the robotic system and used to process and present the collected data. Examples of physician metadata may include, but are not limited to, name, age, organization, years of experience, number of cases per year, total number of cases, techniques / surgeries used (e.g., aspiration or stent retrievers used in mechanical thrombectomy), preferred devices (e.g., conventional guiding catheters or sheath-to-balloon guiding catheters), risk tolerance, and patient population sensitivity.

[0090] A subset of metadata representing data that can be collected from medical procedures or training cases is called case metadata. Examples of case metadata may include, but are not limited to, procedure length (time), subsets or different use cases performed within the procedure, procedure date, devices used, treatment techniques / operation sequence, patient age, case type, treatment location, access location (femoral, radial, carotid, etc.), angiography used, radiation emitted (fluoroscopy time), images taken (e.g., real-time and reference fluorescence images), robot manipulation time, robot device loading time, robot setup time, robot movement, load, outcomes and clinical assessment metrics before, during and after treatment.

[0091] As used herein, the term "kinematic parameters" refers to kinematic parameters and includes translational and rotational displacements, velocities, accelerations, and the time histories of these parameters (i.e., displacement(t), velocity(t), acceleration(t)) and any functions of these parameters, such as the frequencies of displacement, velocity, and acceleration. Kinematic parameters can be integrated or differentiated with respect to time to obtain other kinematic parameters. For example, velocity can be determined by differentiating displacement data with respect to time, acceleration can be determined as the second derivative of displacement with respect to time, velocity can be determined as the integral of acceleration over time, and displacement can be determined as the integral of velocity over time.

[0092] In various examples, the data capture system includes a sensor system and a data acquisition system. The sensor system includes sensors to detect motion and / or load parameters, and the data acquisition system records and / or displays the sensor outputs. The data acquisition system may be equipped with a reference timing unit to record the time associated with each data point. Additionally, it may be equipped with a signal conditioning unit to filter and amplify the signal. The sensor system may include motion sensors and load sensors. Motion sensors are sensors that detect motion parameters. Contact motion sensors include, but are not limited to, accelerometers, LVDTs, and encoders that are directly or indirectly connected to an EMD. Non-contact motion sensors include, but are not limited to, CMOS sensors, optical encoders, ultrasonic sensors, and standard or high-speed cameras. Load sensors are sensors that measure force and / or torque.

[0093] In various examples, the data acquisition system is capable of capturing motion parameters. Motion parameters are equivalent to kinematic parameters and include linear and rotational displacements, velocities, accelerations, and the time histories of these parameters (i.e., displacement(t), velocity(t), acceleration(t)) as well as any other products and derivatives of these parameters, such as the frequencies of displacement, velocity, and acceleration. The data acquisition system captures motion parameters over time such that it also captures the time history of each of these parameters. Motion parameters can be integrated or differentiated with respect to time to obtain other motion parameters. For example, velocity can be obtained by differentiating displacement data with respect to time, acceleration can be obtained as the second derivative of displacement with respect to time, velocity can be determined as the integral of acceleration over time, and displacement can be determined as the integral of velocity over time.

[0094] The data acquisition system is capable of capturing load parameters, including force and torque parameters, as well as the time history of these parameters (i.e., force(t) and torque(t)). The data acquisition system captures load parameters over time, thus capturing the time history of each of these parameters.

[0095] In one example, a data capture system can simultaneously capture both force (e(t)) and flow rate (f(t)) to measure power. The measured power can be used to create a power profile. In the mechanical domain, power is the product of force (F(t)) and velocity (V(t)), or in rotational forms, the product of torque (t) and angular velocity ω(t). In the electrical domain, it can be calculated as the product of voltage (v(t)) and current (i(t)). Power can be converted between energy domains, and models used to describe power flow within multi-domain systems (often represented by bond diagrams) may also include resistance (R), inertia (I), and compliance (C) components. For linear mechanical systems, force is simply force, and flow rate is simply velocity. For angular mechanical systems, force is torque, and flow rate is angular velocity. For electromagnetic systems, force is voltage, and flow rate is current.

[0096] The target operator or reference operator of the data capture system and medical robotic system is an individual experienced in performing medical procedures, such as an interventional physician, radiologist, or surgeon. However, for comparative purposes, data related to other types of operators may be captured. Furthermore, the reference operator can be an individual from whom data is captured. Reference operators may include, but are not limited to, experienced physicians familiar with vascular interventions.

[0097] The data processing unit creates one or more profiles based on the captured data and metadata. A motion profile is formed by one or a combination of multiple motion and / or load patterns associated with the manipulation of the EMD, patterns referred to in the literature as techniques such as synchronized motion (e.g., drilling technique). The master profile can be formed using any combination of smaller profiles such as motion profiles, power profiles, load profiles, case metadata, and physician profiles.

[0098] In some examples, the captured data can be used to provide adaptive guidance during training, simulation, or live surgery performed by the same or different operators. In various examples, the system can provide guidance by providing information to the operator or by applying constraints and rules to the operator. The operator may be able to exceed some guidance but not others, including certain constraints or rules. Examples may include operational constraints (e.g., on load and speed, on displacement, etc.) or constraints on the sequence of steps, the device to be used, or combinations of movements for certain situations.

[0099] The term "adaptive guidance" refers to proactive and responsive guidance provided to the operator during surgery. It can be used during training, simulations, or live surgery performed by the same or different operators. The content and type of guidance may be updated over time as operators gain more experience, or as devices improve and new technologies emerge. Guidance provided to the operator by the system may include limitations and rules within the environment of the surgery being performed. The operator may be able to exceed some guidance without exceeding others, such as certain limitations or rules. Examples include operational constraints (e.g., load, speed, displacement, etc.) or the sequence of steps, or the devices used, or combinations of movements for certain situations.

[0100] Data capture system

[0101] Various examples can be found in, for example Figure 4 The exemplary system is implemented on system 100 shown. It can be a standalone system or can be implemented as part of a robotic medical system, such as the one referenced above. Figure 1-3 System 10 is described. For example, Figure 4 The exemplary system 100 may be implemented as part of the bedside unit 20, control station 26, and / or control computing system 34 of system 10.

[0102] Figure 4 The data acquisition system 120 includes a sensor system 122 and a processing unit 124. For example... Figure 5 As shown in the example, the data acquisition system 120 may also include a device (EMD) interface 110. Various examples of the EMD interface 110, sensor system 122, and processing unit 124 are described in further detail below.

[0103] EMD interface

[0104] Exemplary system 100 includes an EMD interface 110 to receive input from an operator, such as a practitioner, via an input module 220. See the following reference... Figure 5 The input module 220 may include various types of input devices, such as joysticks or other tactile input devices. The EMD interface 110 manipulates the EMD based on commands received from the input module 220. These commands are created by the input module 220 based on operator input to the input module 220 and transmitted to the EMD interface 110. The EMD interface 110 may be part of the robot actuator 24, and the input module 220 may be as described above. Figure 1-3 This describes a portion of the control station 26 of the exemplary system 10. Various examples of the EMD interface 110 are described in further detail below.

[0105] In one embodiment, the data capture system 120 is coupled to a robotic medical system that may include an elongated medical device (EMD). The robotic medical system may be similar to the one referenced above. Figure 1-3 The bedside unit 20 described, or a part of the bedside unit 20. For example, the robot EMD may include the robot actuator 24 of the bedside unit 20.

[0106] As described above, the data capture system 120 of the exemplary system 100 can be implemented in a robotic medical system. In various examples, the data capture system 120 can be implemented within various parts of the robotic medical system. For example, in Figure 1-3 In the exemplary system 10, certain portions of the data acquisition system 120 may be located in the control station 26, the bedside unit 20 (e.g., within the robot actuator 24), or the control computing system 34. For example, the sensor system 122 may be implemented within the device module 32, and the processing unit may be implemented within the control station 26.

[0107] In one example, such as Figure 5As shown, the data capture system 120 may be part of the robotic medical system 200 of the exemplary system 10 described above. Such a data capture system can be used to capture load and motion parameters applied to the EMD during robotic vascular interventional surgery. The robotic system 200 has an input module 28 to receive motion commands for the EMD from the operator. In this respect, mechanical inputs from the operator (e.g., movement of control devices) are coupled and transmitted to corresponding outputs or commands (e.g., catheter movement). In another example, the input module 28 receives digital inputs from the operator to actuate the EMD accordingly. In this respect, inputs from the operator may be received as digital signals or converted into digital signals. These signals can be transmitted, for example, via the control computing system 34 of the robotic system 200. The robot actuator 24 of the medical robot system 10 actuates the EMD based on the motion commands received from the input module 28. The data capture system 120 of the robotic system 200 includes a sensor system 122 to detect load and motion parameters applied to the EMD actuated by the robot actuator 24. The data capture system 120 also includes a processing unit (processing unit 124) for recording and post-processing the captured data. Processing unit 124 processes the captured data and combines it with case metadata and physician metadata to generate an operator profile. Processing unit 124 can further process the profile to generate operating rules / restrictions. The robotic system 200 can use the newly generated rules / restrictions to update existing operating rules / restrictions defined by the robotic system 200. The robotic system 200 allows operators to exceed operating rules / restrictions by inputting numerical values ​​of characteristic parameters and / or by applying physical / mechanical inputs to the EMD interface coupled to the data capture system 110.

[0108] Sensor system

[0109] like Figure 4 As shown in the example, the data capture system 120 includes a sensor system 122 and a processing unit 124. The sensor system 122 may include: one or more sensors to detect motion and / or load parameters applied to the EMD associated with input from the operator; and a mechanical fastener interfaced with the EMD. Although both the sensor system 122 and the processing unit 124 are part of the data capture system 120, they may be physically located in different places and operate at different times. Various types of sensors can be provided to detect a variety of parameters. For example, sensors can be provided to detect motion (e.g., linear displacement, linear velocity, linear acceleration, rotational displacement, rotational speed, or rotational acceleration) or load (e.g., linear force or rotational torque). For example, various sensors may be able to detect other parameters, such as the frequency of the input.

[0110] In one example, a sensor system 122 is provided to capture motion and loading parameters of the EMD when it is directly manipulated by an operator. Therefore, the sensor system 122 is capable of detecting forces or torques applied by the operator or motion parameters (e.g., displacement, velocity, acceleration) introduced by the operator. In other examples, the parameters detected by the sensor system 122 may be correlated with the EMD's response to operator input. For example, the sensor system 122 may detect displacement, velocity, acceleration, or reactive load of the conduit in response to operator input.

[0111] Any of a variety of sensors can be incorporated into sensor system 122. For example, sensor system 122 may include contact sensors and / or non-contact (or contactless) sensors. Contact sensors may include, but are not limited to, accelerometers, linear variable differential transformers (LVDTs), encoders, or load sensors, such as piezoelectric sensors or strain gauge-based sensors, that are directly or indirectly connected to the EMD. Non-contact sensors may include, but are not limited to, complementary metal-oxide-semiconductor (CMOS) sensors, non-contact optical encoders, ultrasonic sensors, standard or high-speed cameras, optically based load sensors, or magnetically based load sensors. In one example, sensor system 122 may condition signals from the sensors to facilitate use by processing unit 124. For example, sensor system 122 may perform smoothing functions, such as root mean square (RMS), to eliminate fluctuations or disturbances in signals from various sensors. In another example, the signal conditioning unit may be equipped with a low-pass filter and / or an amplifier to accordingly filter out high-frequency noise and amplified signals from the signal.

[0112] Data captured by sensor system 122 can be stored for processing by processing unit 124 or another processor. In this regard, the data can be stored in the storage device of data capture system 120 or on an external storage device independent of data capture system 120. Stored data can be retrieved from the storage device when needed.

[0113] In one example, the data acquisition system has a timing unit, such as a hardware clock source, that reports the time associated with each data point. The sensor's data points are stored along with their corresponding times. In one example, the data is stored at a constant sampling rate, meaning the time between each data point is constant and known from the clock source. Therefore, the data is stored as a function of time (e.g., displacement(t), velocity(t), acceleration(t), force(t), torque(t)), and the time history of each sensed parameter is available for further processing. Through further processing of the data, quadratic parameters that are not directly measured are found. As an example, the frequencies of displacement, velocity, and acceleration can be determined from the time histories of these parameters. As another example, velocity can be obtained by differentiating the displacement data with respect to time, acceleration can be obtained as the second derivative of displacement with respect to time, velocity can be determined as the integral of acceleration over time, and displacement can be determined as the integral of velocity over time. The sampling rate can be adjusted based on the frequency of the sensed parameter.

[0114] Sensor system 122 may include any of a variety of sensors to capture desired parameters associated with user input. Sensor system 122 is provided to accurately capture and record the dynamic motions and loads that the physician will use when manipulating the proximal manipulator. In this regard, the primary measurements are force, torque and its rate of change, displacement, linear velocity and acceleration, rotational velocity and acceleration.

[0115] In one example, a sensor system comprising a force sensor and a mechanical fixation device interfaced with an EMD can be used to measure force. The bottom of the force sensor is fixed to a substrate (ground). The mechanical fixation device is attached to the force sensor to provide a frictional interface with the EMD mounted on top of the sensor for force measurement. The interface with the EMD may depend on the geometry of the EMD and the clinical case scenario to be captured. For example, the frictional interface may include a spring-loaded friction clamp. The friction clamp is made of a material that allows the EMD to slide smoothly through the friction clamp. To prevent buckling of the END, the END is supported in the lateral direction. As an example, in the design, two rows of locating pins may serve as guides for the EMD to provide support. The mechanical fixation device, used as the interface with the EMD, is designed to apply an adjustable resistive load to the EMD when the operator manipulates the EMD and to sense and store load and motion parameters. The operator can adjust this resistive load to simulate different load and motion scenarios that occur, for example, in actual vascular interventions without manual intervention.

[0116] In one example, torque measurement can be achieved by using one or more modules to measure the torque on a torsionally oriented EMD. Similar to the force measurement module, the torque measurement module includes an interface and a sensor. This sensor can directly measure torque or convert reaction force into torque. A torque sensor is provided to allow the EMD to rotate continuously when adjustable torque resistance is applied to it, or to simulate the EMD with a certain degree of compliance when fixed at a distal end due to high torque resistance or being jammed by something. In another embodiment, motor or actuator current can be used to calculate the load applied to the EMD.

[0117] Archive generation

[0118] As described above, the use of a robotic medical system by one or more operators can facilitate the operation of the robotic medical system. In this regard, a processing unit 124 of the data capture system 120 is provided to process parameters captured by the sensor system 122 to aid in the future or further operation of the EMD. In one example, the data captured by the sensor system 122 is used to generate a profile and associate the profile with the operator's characteristics (physician metadata), and / or associate the profile with the characteristics of the medical record (medical record metadata). Figure 4 As shown, the file, along with its association with various parameters, can be stored in the file module 130. The file can be used to facilitate the operation of various devices for training, simulation, or live surgery via training systems, simulators, or robotic medical systems.

[0119] Figure 6 The diagram illustrates a method for generating and associating files. In exemplary method 300, parameters associated with user input are captured by sensor system 122 of, for example, data capture system 120 (box 310). The captured parameters can be associated with any one or a combination of multiple inputs. In one example, the parameters are associated with discrete user inputs, which can be any kind of motion or load parameter. For example, the captured parameters can be associated with discrete linear velocity, linear force, rotational speed, or rotational torque. In a particular example, the captured parameters can be associated with individual inputs in six-dimensional velocity and six-dimensional force / torque. Thus, sensor system 122 can distribute the measurements to different modules that can be positioned on a table. Similar to a clinical setting, a physician can operate the system while standing beside the table, where each sensor module is located relative to the physician's position. Sensor data can be collected at the proximal end of the EMD, where the EMD is being manipulated by the operator.

[0120] In another example, the captured parameters can be associated with various combinations of user input. In a specific example, the captured parameters are associated with combinations of linear velocity and rotational velocity (e.g., drilling motion), linear force and rotational torque, linear velocity and linear force, and / or rotational velocity and rotational torque. When capturing combinations of load and speed, new product parameters can be determined, such as a power parameter as the product of load and speed. In various examples, various parameters of the combinations are measured simultaneously.

[0121] In yet another example, the captured parameters can be associated with various combinations of any number of user inputs. For instance, the captured parameters can be associated with any combination of linear motion, linear load, rotary motion, and / or rotary load.

[0122] In one example, data capture system 120 captures parameters from a single EMD. In this case, one or more EMDs can be nested / assembled to represent the actual setup of the EMDs during actual surgery; however, motion and load parameters are captured from a single EMD. In another example, more than one EMD is nested / assembled, and sensor system 122 uses sensors to capture concurrent data from more than one EMD. As an example, the data capture system captures the relative motion (referred to as differential motion) of two or more EMDs and / or the relative loads of two or more EMDs, such as differential force and torque.

[0123] Refer again Figure 6 In an exemplary method 300, the captured parameters are converted into at least one file (box 320). In one example, processing unit 124 may generate a file based on captured data associated with a single reference operator. In this respect, the file may be based on one or more surgeries performed by the reference operator. The file may be updated or modified using each subsequent surgery performed by the reference operator. In this respect, processing unit 124 may utilize algorithmic analysis of inputs from one or more operators when forming the file.

[0124] In other examples, processing unit 124 may generate profiles based on captured data from multiple operators. In one example, captured data associated with a reference operator may be combined with captured data associated with other operators. Processing unit 124 may generate profiles based on experience level or other characteristics by combining data associated with multiple operators using algorithmic analysis. In one example, data from each operator may be weighted based on each operator's characteristics. For example, an operator with a higher experience level may have a greater weight than another operator with a lower experience level. Weighting can also be used to generate profiles for specific experience levels. For example, a profile for n years of experience may be generated such that the weight of an operator with approximately n years of experience is greater than the weight of an operator with fewer years of experience. Thus, in one example, separate profiles may be generated for experience levels of approximately 5 years, approximately 10 years, approximately 15 years, etc. For a profile corresponding to 15 years of experience, the weight of an operator with 10 years of experience may be higher than that of an operator with 5 years of experience. Similarly, weighting may be applied to provide profiles associated with any of the various operator characteristics. In one example, the profile is based on a combination of reference operator characteristics, patient characteristics, anatomical data, physiological data, endovascular device characteristics, surgical characteristics, technical characteristics, imaging data, and surgical outcomes. The profile can be updated or generated by combining this data with additional data associated with other practitioners, procedures, or patients. In one example, the profile can be updated periodically or continuously (on an ongoing basis) using successive surgeries.

[0125] In one example, the profile generated by processing unit 124 is a power profile based on motion and load parameters associated with input from the operator. In one example, the profile may include power across six dimensions (three linear and three rotational dimensions) throughout the surgery. In this respect, the profile may be a continuous profile of every point in the surgery, or it may include discrete points representing various stages of the surgery. In one example, the profile generated by processing unit 124 may be based on a heuristic model. This heuristic model may be based on data captured from one or more surgeries.

[0126] Refer again Figure 6In exemplary method 300, the file is associated with the operator's characteristics (box 330). In one example, the file is associated with the operator's metadata. For example, the captured data may be associated with the operator's identity (e.g., name), age, experience level, or specialty. In other examples, the captured data may be associated with the surgery in which the data was captured. In this regard, the captured data may be associated with anatomical structures, patient characteristics, device specifications, type of surgery, technique used, or surgical outcome. In other examples, the file may be associated with the case metadata of the surgery. For example, case metadata may include anatomical structures, anatomical locations, patient characteristics, device type, device specifications, type of surgery, specific parts of the surgery, physician descriptions (e.g., name, age, number of cases per year, specialty, and experience), technique used, or surgical outcome.

[0127] Figure 6 The exemplary method 300 can be implemented on a computer or another electronic device. Furthermore, the various steps of the exemplary method 300 can be implemented as instructions stored on a non-transitory computer-readable medium. These instructions can be executed by a processor of a computing system.

[0128] Adaptive boot

[0129] In the above example, processing unit 124 uses data captured by sensor system 122 to generate a profile associated with the operator's characteristics. In another example, data captured by sensor system 122 is used to generate guidance parameters that can help the operator use the robotic EMD, for example, in future surgeries. For example, data captured from a reference operator or a group of operators can be used to generate guidance parameters associated with motion, load, or power parameters related to user input. Guidance parameters can translate into, for example, limits on any of the following parameters: linear velocity, linear force, rotational speed, rotational torque, or a variety of other parameters. In another example, adaptive guidance can be accomplished through rules and relationships between more than one parameter. For example, a speed limit could be a function of the load acting on the EMD. In such an example, the maximum permissible speed can be reduced when the load is considered high to enhance surgical safety. In one example, the limit is consistently applied throughout the surgery. In another example, the limit is variably applied throughout the surgery. Furthermore, guidance parameters can vary based on any of a variety of factors, including but not limited to the position of the elongated medical device relative to the human body, the surgical environment, the patient's age, the direction of movement of the EMD, or the level of load applied by the operator.

[0130] Figure 7The diagram illustrates an exemplary method associated with adaptive guidance. According to exemplary method 400, captured parameters associated with user input are received for processing (box 410). As described above, the captured parameters may be associated with input from one or more practitioners and may be based on detection by a sensor system. The captured parameters may be stored in a memory device or transferred to a processor, such as processing unit 124.

[0131] according to Figure 7 In an exemplary method 400, the captured parameters are used to generate adaptive guidance parameters for use with a robotic medical device (box 420). In one example, processing unit 124 may generate guidance parameters that define an operational envelope associated with, for example, surgical characteristics, patient characteristics, or operator characteristics. For example, the guidance parameters may determine linear velocity limits based on the operator's level of experience. In this respect, the guidance parameters may impose stricter limits for less experienced operators and looser limits for more experienced operators. In other examples, the guidance parameters may determine limits based on the patient's age. In this respect, the limits may be more stringent for very young or very old patients.

[0132] Similarly, guidance parameters can vary depending on the stage of the surgery. In one example, adaptive guidance parameters provide a constant level of guidance throughout the surgery. For instance, adaptive guidance parameters can provide constant limits on various inputs (e.g., force, torque, linear velocity, or rotational velocity) at each stage of the surgery. In other examples, these limits can vary throughout the surgery. For example, the limit on linear velocity might be more stringent when approaching fragile anatomical structures, or relaxed otherwise.

[0133] Adaptive guidance parameters can be used to facilitate operator control of the robotic medical device (box 430). In this regard, alerts or other forms of guidance can be provided to the operator during surgery based on the guidance parameters.

[0134] Furthermore, in various examples, operators may be given the option to accept or exceed the restrictions defined by the guiding parameters. One or more constraints (e.g., limits) may be critical enough to disallow overridden options, while other constraints are left to the operator's discretion.

[0135] As described above, in some examples, guidance parameters may be reflected as constraints. In other examples, guidance parameters may be reflected as operating rules, control equations, surgical recommendations, motion profiles, rule-based motion and load values, or any of a variety of other forms. Motion profiles may include synchronized motions associated with operator input. Various profiles may be based on a database associated with operator input and may indicate synchronized motion patterns associated with one or more EMDs from operator input.

[0136] In one example, adaptive guidance parameters can be modified or updated based on additional data associated with other practitioners, surgeries, or patients. In another example, adaptive guidance parameters can be updated periodically or continuously (on an ongoing basis) using successive surgeries. For example, restrictions on various operator inputs can be tightened or relaxed based on additional surgical data.

[0137] and Figure 6 The exemplary method 300 is the same. Figure 7 The exemplary method 400 can also be implemented on a computer or another electronic device. Furthermore, the various steps of the exemplary method 400 can be implemented as instructions stored on a non-transitory computer-readable medium. These instructions can be executed by a processor of a computing system.

[0138] Robotic systems with data capture systems

[0139] Now for reference Figure 5 The illustration depicts a schematic diagram of an exemplary robotic medical system with an exemplary data capture system according to an embodiment. In this respect, although Figure 4 The illustration shows a system 100 that can be provided as a standalone system that can be coupled to a robot EMD, but... Figure 5 The illustration shows a robotic medical system 200 that incorporates a data capture system.

[0140] therefore, Figure 5 The robotic medical system 200 is equipped with a data acquisition system 120 and an EMD interface 110. Similarly, the data acquisition system 120 includes a sensor system 122 and... Figure 4 The data acquisition system 120 includes a processing unit 124. Furthermore, the robotic medical system 200 is equipped with one or more EMDs, which are controlled by a robot driver 24. The robot driver 24 responds to commands from the input module 220.

[0141] Subsequently, the EMD interface 110 can respond to operator input received via the input module 220. The input module 220 may include a physical or tactile input device controlled by the operator. The operator input to the input module 220 can be converted into mechanical or digital input to the EMD interface 110.

[0142] Figure 5 An exemplary robotic medical system 200 may be similar to the one referenced above. Figure 1-3 The system 10 described may include a bedside unit and a control station. A portion of the input module 220 and the data capture system 120 may be located in the control station, while the one or more EMDs are located on the bedside unit.

[0143] In one example, the robotic medical system 200 is equipped with a single EMD. In other examples, the number of EMDs can be selected for a specific purpose or procedure. Multiple EMDs can be arranged in series, in parallel, or in any other desired configuration. In one example, using multiple EMDs arranged in series, user input can be applied to the first EMD in the series, and commands are relayed through that first EMD to subsequent downstream EMDs. In another example, using multiple EMDs arranged in parallel, user input from the operator is provided directly to each EMD. Of course, some examples may include multiple EMDs arranged in a combination of series and parallel. In a system with multiple EMDs, the EMD interface 110 and input module 220 allow the operator to operate multiple EMDs simultaneously. Similarly, the sensor system 122 is capable of simultaneously detecting and capturing motion and load parameters associated with operator input applied by the robotic system to multiple EMDs.

[0144] Figure 5 The robotic medical system 200 is equipped with a data capture system 120 and an EMD interface 110 to perform the above-mentioned functions. Figure 4 The document describes the capabilities for generating medical records and adaptive guidance. Of course, the generation of medical records and adaptive guidance parameters can be performed in conjunction with training, simulation, or live surgery. Furthermore, the generation of medical records and adaptive guidance parameters can be performed as a batch function after data is captured during surgery. In some examples, data capture, document generation, and adaptive guidance parameter generation can be performed independently on the same robotic medical system 200 or on different systems 200. Moreover, the medical records and adaptive guidance parameters generated based on data captured on one robotic medical system 200 can be used to facilitate the operation of other robotic medical systems 200 and / or the operation of EMD in manual cases. In this respect, once the medical records and / or adaptive guidance parameters are generated, they can be disseminated for use by operators of various other robotic medical systems 200 and / or operators of manual surgeries.

[0145] As described above, the data capture system 120 of the robotic medical system 200 can be coupled to the control computing system 34 of the robotic medical system 200 to generate and / or update files, operating rules, and restrictions. In other examples, the data capture system can be coupled to the training system 230 or the simulator 240 to facilitate the training of various operators.

[0146] Now for reference Figure 8 The illustration depicts an exemplary data input arrangement and data utilization of a robotic medical system with an EMD according to an embodiment. Exemplary arrangement 500 illustrates the use of... Figure 4 Exemplary data capture system 100 or Figure 5 The data stream of the robotic medical system is 200. For example... Figure 8 As shown, data from experienced physician 510 can be obtained during on-site surgery via measurement system 512 (e.g., Figure 5 The sensor system 122 is used to capture the data. Alternatively, the data may be collected during the training phase or during simulation on the simulator / trainer 522. The captured data is collected, recorded, and processed by 514. The captured data can be used to generate physician profiles 516. One or more physician profiles 516 can be used to generate public profiles. For example, as described above, public profiles can be generated for association with specific levels of experience.

[0147] The newly captured files can be used to update operating rules and restrictions 518. In this regard, robotic medical systems can use these files to teach or guide other operators or to limit various parameters of the robotic medical system.

[0148] like Figure 8 As shown, a feedback loop can be provided, where the use of the robotic system can be used to collect, record, or process additional data. This additional data can be used to continuously update physician records.

[0149] In one example, a robotic medical system can be used to obtain limits on the load and motion parameters of an EMD applied to robotic manipulation. The EMD may be damaged during operator manipulation under specific loads, for example, due to buckling, kinking, or fracture. Appropriate ranges for load and motion parameters, such as force, torque, velocity, acceleration, displacement, and combinations thereof, depend on the mechanical characteristics of the EMD and its boundary conditions, such as how the EMD is supported. For an EMD manipulated by a robotic system, in addition to the mechanical characteristics of the EMD, appropriate ranges for load and motion parameters to avoid damage to the EMD also depend on the design and characteristics of the robot drive system. In an exemplary embodiment, Figure 5 The robotic system 200 uses a data capture system to obtain appropriate ranges of load and motion parameters on the EMD while being manipulated by the robotic medical system. These appropriate ranges can be found during potentially destructive or non-destructive testing. The data capture system stores the captured data during such testing and uses this data when generating operating rules and limits for the robotic manipulation of the EMD. For such testing, the data capture system may use one EMD or an arrangement of two or more EMDs. This arrangement may involve serial or parallel manipulation of the EMDs. Furthermore, the processing unit 130 considers other factors, such as constraints of the medical robotic system, to adjust the operating rules and limits. For example, when latency exists in the system, the processing unit 130 may reduce the maximum linear and rotational speeds of the EMDs; for example, this may be due to network latency associated with remote input modules.

[0150] According to an embodiment, the data acquisition system can simultaneously capture one or more combinations of linear and rotational motion parameters and force and torque parameters applied to the EMD. Such a data acquisition system can be standalone, such as... Figure 4 As shown, it can also be coupled to a robotic medical system, such as Figure 5 As shown in the diagram. In one embodiment, the robot system uses a data capture system that operates in two states. When the robot system is used to manipulate the EMD via input module 220 (e.g., during surgery or simulation), the data capture system operates in a first state. In this first state, the data capture system captures and stores the motion and load parameters applied to the EMD by the robot system. In the second state, the EMD is loaded into the robot system, but it is directly manipulated by the operator. In other words, the operator can apply mechanical input to the EMD when it is engaged with the robot system equipped with the data capture system. In this second state, the robot system does not manipulate the EMD; instead, it applies an adjustable resistive load to the EMD to resist its motion. The operator can adjust the resistive load applied to the EMD by the robot system to create different load scenarios. Similar to the first state, when the user directly manipulates the EMD, the data capture system captures the load and motion parameters applied to the EMD. The robot system generates a profile, as well as operating rules and limitations, based on the data captured in states 1 and 2, or a combination of data captured in both states. Such a robotic system allows for the customization of load and motion profiles, as well as operating rules / restrictions, based on the operator's mechanical input on the EMD, without the need for an additional, separate data capture system.

[0151] As an example of such a robotic system having the two states described above, in state 2, the EMD can be engaged in the device module 32 via a chuck. The chuck holds the EMD such that the EMD does not move relative to the chuck. Alternatively, the entire device module 32 is allowed to move linearly with the chuck and EMD in response to a force mechanically applied to the EMD by the operator. Furthermore, the chuck is allowed to rotate in response to a torque applied to the EMD. Despite the allowed linear and rotational movement of the EMD, actuators generate an adjustable resistive load to counteract the movement of the EMD. A data capture system allows independent resistance and torque to be applied to the EMD. As an example, the current of the actuators can be adjusted to adjust the resistive load applied to the EMD by the device module 32. The load parameters can be determined by measuring the current of the actuators, since the load of the actuators is proportional to its current. As another example, brakes can be used on each actuator to generate an adjustable load on the EMD. As yet another example, the device module 32 does not move and only captures load data applied to the EMD by the operator. In yet another example, sensors can be used to measure the load parameters. A sensor for measuring torque is attached between the actuator for rotational degrees of freedom and the chuck holding the EMD. A sensor for measuring force may be placed between the chuck and device module 32 or between device module 32 and the base of the sliding component for linear degrees of freedom of the EMD. As another example, the EMD has an embedded load sensor to measure load parameters.

[0152] Exemplary hardware

[0153] Now for reference Figure 9-11 The illustration shows various examples of hardware used in conjunction with the exemplary robotic medical system or data capture system described herein. First, refer to... Figure 9 The illustration depicts an exemplary actuator / sensor arrangement for use with various EMDs, according to an embodiment. Figure 9 The exemplary arrangement 600 shown can be used to measure force and linear velocity simultaneously using a single module. Furthermore, the exemplary arrangement 600 can be used to measure torque and rotational speed simultaneously.

[0154] An exemplary arrangement 600 is illustrated with an EMD 610 passing through it. The EMD 610 is held by an adjustable friction clamp 620. The clamp 620 may include a spring-loaded pad and / or a tire that pushes against the EMD 610, allowing continuous movement of the EMD 610. The frictional resistance can be adjusted using, for example, a thumbscrew or a motor system with servo control. An optical sensor 630 is also used to measure the motion parameters of the EMD.

[0155] The exemplary arrangement 600 also includes a torque converter 640 for clamping the EMD. The operator uses the back of the torque converter ( Figure 9The EMD is manipulated by the torque converter (located on the far right of the torque converter). The torque converter has one or more sensors 650 to measure the load (force and torque) applied to the EMD through the torque converter. Data is captured simultaneously from optical sensors 630 and 650.

[0156] Now for reference Figure 10 The illustration depicts an exemplary linear sensor system module for use with various EMDs, according to an embodiment. An exemplary linear module 700 is illustrated as having an EMD 710 passing through it. The exemplary linear module 700 includes a friction clamp 720. As described above, the friction clamp 720 allows continuous movement of the EMD 710 through the linear module 700. The friction clamp 720 includes a spring 722 to provide a clamping force to the EMD 710. This clamping force can be adjusted using a thumbscrew 724.

[0157] An exemplary linear module 700 includes an optical encoder 740 to measure linear displacement and / or linear velocity and / or acceleration. The optical encoder 740 is coupled to a pair of tires 730. The pair of tires 730 clamp the EMD using torque springs. As the EMD moves linearly (forward or backward), the tires rotate accordingly, and the optical encoder 740 measures the rotational speed of the tires. Given the rotational speed of the tires and knowing the tire diameter, the processing unit 124 of the data acquisition system 120 determines the linear velocity of the EMD. Furthermore, a force sensor 750 is provided to measure the linear force applied to the EMD 710.

[0158] Now for reference Figure 11 The illustration depicts an exemplary rotary sensor system module for use with various EMDs, according to an embodiment. An exemplary rotary module 800 is illustrated as having an EMD 810 passing through it. The exemplary rotary module 800 includes a friction clamp 820 having a clamping plate that allows the EMD 810 to undergo continuous rotational movement through the rotary module 800. The friction clamp 820 applies an adjustable torque to the EMD. The resistive torque applied to the EMD can be adjusted, for example, using a screw. A spring can be used in the friction clamp 820 to form an adjustable clamping system.

[0159] An exemplary rotation module 800 includes an encoder 840, such as an optical encoder, to measure rotational displacement, rotational speed, and / or rotational acceleration. Additionally, a torque sensor 830 is provided to measure the torque applied to the EMD 810. The simultaneous capture of torque and motion parameters from the encoder 840 and the torque sensor 830 can be used to obtain the rotational power applied to the EMD.

[0160] Computer-executable instructions for the steps of exemplary methods 300 and 400 may be stored on a computer-readable medium of one form. A computer-readable medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information such as computer-readable instructions, data structures, program modules, or other data. Computer-readable media include, but are not limited to, random access memory (RAM), read-only memory (ROM), electrically erasable programmable ROM (EEPROM), flash memory or other storage technologies, optical disc ROM (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic tape cassettes, magnetic tape, disk storage or other magnetic storage devices, or any medium that can be used to store desired instructions and can be used by system 10 (…). Figure 1 (as shown in the image) any other medium for access, including access via the Internet or other computer networks.

[0161] This written description uses examples to disclose the invention, including the best mode, and also enables any person skilled in the art to make and use the invention. The patentable scope of the invention is defined by the claims and may include other examples that would occur to a person skilled in the art. Such other examples are intended to fall within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements that do not substantially differ from the literal language of the claims. According to alternative embodiments, the order and sequence of any process or method steps may be altered or reordered.

[0162] Many other changes and modifications may be made to this invention without departing from its spirit. The scope of these and other changes will become apparent from the appended claims.

[0163] Clause 1: A data capture system for generating a profile using capture parameters from a reference operator, comprising: a user interface for receiving input from the reference operator for operation of one or more elongated medical devices (EMDs); a sensor system having sensors for capturing parameters associated with the input from the reference operator; and a processing unit for using the capture parameters to generate at least one profile associated with characteristics of the reference operator.

[0164] Clause 2: A robotic medical system comprising: a module for independently and collaboratively actuating one or more EMDs; a user interface for receiving input from a reference operator to manipulate the EMDs; a sensor system having sensors for detecting motion and / or load parameters applied to the EMDs; a data acquisition section for capturing parameters detected by the sensors and associated with the input from the reference operator, the captured parameters including at least one motion or load parameter, wherein the data acquisition section correlates the captured parameters with characteristics of the reference operator; and a processing unit for converting the detected parameters into operational control equations for the elongated medical device and surgery.

[0165] Clause 3: A method comprising: capturing input parameters from a reference operator of a robotic device, the captured input parameters including at least one motion or load parameter; converting the captured input parameters into operating commands for the robotic device; and using the captured input parameters to generate a profile associated with characteristics of the reference operator.

[0166] Clause 4: A non-transitory computer-readable storage medium encoded with instructions executable by a processor of a computing system, the computer-readable storage medium comprising the following instructions: capturing input parameters from a reference operator of a robotic device, the captured input parameters including at least one motion or load parameter; converting the captured input parameters into operating commands for the robotic device; and using the captured input parameters to generate a file associated with characteristics of the reference operator.

[0167] Clause 5: A computer-implemented method comprising: capturing input parameters from a reference operator of a robotic device, the captured input parameters including at least one motion or load parameter; converting the captured input parameters into operating commands for the robotic device; and using the captured input parameters to generate a profile associated with characteristics of the reference operator.

[0168] Clause 6: A data capture system comprising: a user interface for receiving input from a reference operator for operation of an elongated medical device, the user interface including sensors for detecting parameters associated with the input from the reference operator; a recording portion for capturing the parameters detected by the sensors and associated with the input from the reference operator, the captured parameters including at least one motion or load parameter; and a processing unit for generating adaptive guidance parameters for operation of the elongated medical device based on the captured input parameters.

[0169] Clause 7: A robotic medical system comprising: a user interface for receiving input from a reference operator; a sensor system having sensors for detecting parameters associated with the input from the reference operator; a data acquisition section for capturing the parameters detected by the sensors and associated with the input from the reference operator; a processing unit for converting the input from the operator into adaptive guidance for operation of an elongated medical device (EMD) and surgery; and at least one module that independently and cooperatively actuates one or more EMDs.

[0170] Clause 8: A method comprising: capturing input parameters from a reference operator of an elongated medical device, the captured input parameters including at least one motion or load parameter; converting the captured input parameters into an operating command for the elongated medical device; and generating guidance parameters for the elongated medical device based on the captured input parameters.

[0171] Clause 9: A non-transitory computer-readable storage medium encoded with instructions executable by a processor of a computing system, the computer-readable storage medium comprising the following instructions: capturing input parameters from a reference operator of a robotic device, the captured input parameters including at least one motion or load parameter; converting the captured input parameters into operating commands for the robotic device; and generating guidance parameters for an elongated medical device based on the captured input parameters.

[0172] Clause 10: A computer-implemented method comprising: capturing input parameters from a reference operator of a robotic device, the captured input parameters including at least one motion or load parameter; converting the captured input parameters into operating commands for the robotic device; and generating guidance parameters for an elongated medical device based on the captured input parameters.

[0173] Clause 11: A data capture system for generating a profile using capture parameters from a reference operator, comprising: a user interface for receiving input from a reference operator for operation of one or more elongated medical devices (EMDs); and a sensor system having sensors for capturing parameters associated with the input from the reference operator; wherein the parameters detected by the sensors include at least one of: (a) a combination of linear velocity and linear force load; (b) a combination of rotational velocity and rotational torque; (c) a combination of displacement and / or velocity and / or acceleration with linear force; or (d) a combination of angular displacement and / or angular velocity and / or angular acceleration with torque.

[0174] Clause 12: A data capture system for generating a profile using capture parameters from a reference operator, comprising: a user interface for receiving input from a reference operator for operation of one or more elongated medical devices (EMDs); and a sensor system having sensors for capturing parameters associated with the input from the reference operator; wherein the parameters detected by the sensors include a combination of two or more of motion parameters, load parameters, position, displacement, frequency, linear velocity, linear force, rotational speed, or rotational torque.

[0175] Clause 13: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Clauses 1-12, wherein the parameters detected by the sensor include at least one of motion parameters or load parameters.

[0176] Clause 14: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Clauses 1-13, wherein the motion parameters and the load parameters include at least one of displacement, linear velocity, linear force, rotational speed, rotational torque, acceleration, or frequency.

[0177] Clause 15: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Clauses 1-14, wherein the parameters detected by the sensor include at least one of the following: (a) a combination of linear velocity and linear force load; (b) a combination of rotational velocity and rotational torque; (c) a combination of displacement and / or velocity and / or acceleration with linear force; or (d) a combination of angular displacement and / or angular velocity and / or angular acceleration with torque.

[0178] Clause 16: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Clauses 1-15, wherein the parameters detected by the sensor include the manipulation frequency of the EMD.

[0179] Clause 17: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Clauses 1-16, wherein the parameters detected by the sensor include two or more combinations of motion parameters, load parameters, position, displacement, frequency, linear velocity, linear force, rotational speed, or rotational torque.

[0180] Clause 18: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Clauses 1-17, wherein the data capture system is independent or part of another system such as a robotic medical system or a training system.

[0181] Clause 19: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Clauses 1-18, wherein the sensor system comprises contact and / or non-contact sensors for detecting motion and / or load on an EMD or a stack of EMDs.

[0182] Clause 20: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Clauses 1-19, wherein the sensor system may include signal conditioning.

[0183] Clause 21: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Clauses 1-20, wherein the user interface includes more than one EMD, and a sensor system detects input parameters for concurrent operation of more than one EMD.

[0184] Clause 22: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Clauses 1-21, wherein the parameters are captured based on a heuristic model.

[0185] Clause 23: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Clauses 1-22, wherein the characteristics of the reference operator include at least one of physician metadata.

[0186] Article 24: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Articles 1-23, wherein at least a portion of the capture parameters is associated with case metadata.

[0187] Article 25: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Articles 1-24, wherein at least a portion of the capture parameters is a combination of physician metadata and case metadata.

[0188] Clause 26: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Clauses 1-25, wherein the recording and retrieval of data can be local or non-local for the system.

[0189] Clause 27: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Clauses 1-26, wherein the processing unit utilizes algorithmic analysis of inputs from one or more operators when forming the at least one file.

[0190] Clause 28: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Clauses 1-27, wherein the processing unit generates a power profile associated with the at least one profile containing motion and load parameters.

[0191] Clause 29: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Clauses 1-28, wherein the processing unit calculates and determines an envelope of the range of motion, load, and power parameters.

[0192] Clause 30: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Clauses 1-29, wherein the processing unit generates adaptive guidance parameters for manipulating the EMD based on motion and load parameters contained in the at least one file.

[0193] Clause 31: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Clauses 1-30, wherein the processing unit generates motion profiles and / or load profiles associated with one or more EMDs.

[0194] Clause 32: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in Clause 31, wherein the motion profile is constructed solely based on motion parameters of the at least one profile for an EMD, including simultaneous rotational and linear motion of the EMD.

[0195] Clause 33: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in Clause 31, wherein the motion profile is constructed based on motion parameters for at least one profile of more than one EMD, including simultaneous rotational and / or linear motion of a first EMD and rotational and / or linear motion of a second EMD.

[0196] Clause 34: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in Clause 31, wherein the motion profile is constructed based on load parameters for at least one profile of more than one EMD.

[0197] Clause 35: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in Clause 31, wherein the motion profile is constructed based on both motion and load parameters for at least one profile of more than one EMD.

[0198] Article 36: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Articles 1-35, wherein the processing unit generates a master file by combining physician metadata and case metadata.

[0199] Clause 37: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Clauses 1-36, wherein the processing unit combines the capture parameters from the reference operator with additional capture parameters from an additional operator to generate an aggregated archive.

[0200] Article 38: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Articles 1-37, wherein the at least one file generated by the processing unit is updated with additional captured data from another additional operator.

[0201] Article 39: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Articles 1-38, wherein the processing unit updates the file when new input data is available after a series of ongoing surgeries.

[0202] Clause 40: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Clauses 1-39, wherein the processing unit converts input from the reference operator, combined with other metadata, into operating control equations, operating constraints, and commands.

[0203] Clause 41: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Clauses 1-40, wherein the processing unit is capable of generating or updating the at least one file and converting data into operating rules offline or in real time.

[0204] Clause 42: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Clauses 1-41, wherein the processing unit provides feedback to a second operator based on the generated file.

[0205] Clause 43: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in Clause 42, wherein the feedback is provided during training simulation.

[0206] Clause 44: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in Clause 42, wherein the feedback is provided during on-site surgery performed by the second operator.

[0207] Clause 45: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in Clause 42, wherein the second operator is able to selectively accept or reject the feedback.

[0208] Clause 46: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any one of Clauses 1-45, wherein the processing unit generates adaptive boot parameters.

[0209] Clause 47: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in Clause 46, wherein the adaptive guidance parameters include at least one of the following: operational control equations or constraints applied to the EMD or surgery, surgical recommendations, motion profiles, or motion and load based on general rules.

Claims

1. A data capture system that generates archives using capture parameters from a reference operator, comprising: User interface, which receives input from the reference operator for operation of one or more elongated medical devices; A sensor system having sensors for capturing parameters associated with the input from the reference operator, wherein the parameters detected by the sensors include at least one of motion parameters or load parameters; and A processing unit uses the capture parameters to generate at least one profile associated with the characteristics of the reference operator, wherein the characteristics of the reference operator include the reference operator's experience level, wherein data from each operator is weighted based on each operator's experience level to generate a profile for a specific experience level, and wherein operators with higher experience levels have a greater weight than operators with lower experience levels. The processing unit is further configured to combine the parameters associated with the input from the reference operator with other metadata to transform them into operation control equations, operation constraints, and commands, wherein the other metadata includes other data about operator characteristics and case history.

2. The data capture system according to claim 1, wherein, The motion parameters and the load parameters include at least one of displacement, linear velocity, linear force, rotational speed, rotational torque, acceleration, or frequency.

3. The data capture system according to claim 1, wherein, The parameters detected by the sensor include at least one of the following: (a) a combination of linear velocity and linear force load; (b) a combination of rotational velocity and rotational torque; (c) a combination of displacement and / or velocity and / or acceleration with linear force; or (d) a combination of angular displacement and / or angular velocity and / or angular acceleration with torque.

4. The data capture system according to claim 1, wherein, The parameters detected by the sensor include the displacement, velocity, and frequency of acceleration of the elongated medical device.

5. The data capture system according to claim 1, wherein, The parameters detected by the sensor include two or more combinations of motion parameters, load parameters, position, displacement, frequency, linear velocity, linear force, rotational speed, or rotational torque.

6. The data capture system according to claim 1, wherein, The data capture system is either independent or part of another system.

7. The data capture system according to claim 6, wherein, The other system is a robotic medical system or a training system.

8. The data capture system according to claim 1, wherein, The sensor system includes contact and / or non-contact sensors to detect the movement and / or load of a slender medical device or a stack of slender medical devices.

9. The data capture system according to claim 1, wherein, The sensor system includes signal conditioning.

10. The data capture system according to claim 1, wherein, The user interface includes more than one elongated medical device, and the sensor system detects input parameters for concurrent operation of more than one elongated medical device.

11. The data capture system according to claim 1, wherein, The parameters are captured based on a heuristic model.

12. The data capture system according to claim 1, wherein, The characteristics of the reference operator include at least one of the doctor's metadata.

13. The data capture system according to claim 1, wherein, At least a portion of the captured parameters are associated with case metadata.

14. The data capture system according to claim 1, wherein, At least a portion of the captured parameters is a combination of doctor metadata and case metadata.

15. The data capture system according to claim 1, wherein, Data recording and retrieval can be local or non-local for the system.

16. The data capture system according to claim 1, wherein, The processing unit utilizes algorithmic analysis of inputs from one or more operators when forming the at least one file.

17. The data capture system according to claim 1, wherein, The processing unit generates a power profile associated with the at least one profile containing motion and load parameters, wherein the power can be measured based on the force and flow rate simultaneously captured by the data capture system to form the power profile.

18. The data capture system according to claim 17, wherein, The processing unit calculates and determines the envelope of the range of motion, load, and power parameters.

19. The data capture system according to claim 1, wherein, The processing unit generates adaptive guidance parameters for manipulating the slender medical device based on motion and load parameters contained in the at least one file.

20. The data capture system according to claim 1, wherein, The processing unit generates motion profiles and / or load profiles associated with one or more elongated medical devices.

21. The data capture system according to claim 20, wherein, The motion profile is constructed solely based on motion parameters of at least one profile for a slender medical device, including simultaneous rotational and linear motions of the slender medical device.

22. The data capture system according to claim 20, wherein, The motion profile is constructed based on motion parameters of at least one profile for more than one elongated medical device, including simultaneous rotational and / or linear motion of the first elongated medical device and rotational and / or linear motion of the second elongated medical device.

23. The data capture system according to claim 20, wherein, The motion profile is constructed based on load parameters of at least one profile for more than one elongated medical device.

24. The data capture system according to claim 20, wherein, The motion profile is constructed based on both motion and load parameters of at least one profile for more than one elongated medical device.

25. The data capture system according to claim 1, wherein, The processing unit generates the master file by combining doctor metadata and case metadata.

26. The data capture system according to claim 1, wherein, The processing unit combines the capture parameters from the reference operator with the additional capture parameters from the additional operator to generate an aggregated archive.

27. The data capture system according to claim 1, wherein, The at least one file generated by the processing unit is updated with additional captured data from another additional operator.

28. The data capture system according to claim 1, wherein, The processing unit updates the file when new input data becomes available after a series of ongoing surgeries.

29. The data capture system according to claim 1, wherein, The processing unit can generate or update the at least one file and convert data into operation rules offline or in real time.

30. The data capture system according to claim 1, wherein, The processing unit provides feedback to the second operator based on the generated file.

31. The data capture system according to claim 30, wherein, The feedback is provided during the training simulation.

32. The data capture system according to claim 30, wherein, The feedback is provided during the on-site surgery performed by the second operator.

33. The data capture system according to claim 30, wherein, The second operator can selectively accept or reject the feedback.

34. The data capture system according to claim 1, wherein, The processing unit generates adaptive guidance parameters.

35. The data capture system according to claim 34, wherein, The adaptive guidance parameters include at least one of the following: operational control equations or limitations applied to the elongated medical device or surgery, surgical recommendations, motion profiles, or motion and load based on general rules.

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