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

Abstract

The invention relates to data capture and adaptive guidance for robotic surgery with elongate medical devices. A robotic medical system includes a data capture portion that captures a plurality of parameters detected by a sensor system, the plurality of parameters associated with a plurality of inputs from a reference operator; a processing unit that translates the plurality of inputs into operational adaptive guidance for an elongate medical device or a procedure using the elongate medical device, and provides the operational adaptive guidance to an operator during a simulated or on-site procedure by the operator; and at least one module that independently and cooperatively actuates the elongate medical device.

Description

[0001] This application is a divisional application of Chinese patent application No. 202080064586.1, entitled “Data Capture and Adaptive Guidance for Robotic Surgery Utilizing Slender Medical Devices,” filed on July 14, 2020.

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

[0003] The present invention relates generally to the field of robotic medical surgical systems, and more particularly to systems, apparatus, and methods related to capturing data associated with user input and providing adaptive guidance for surgery using elongated medical devices. Background Art

[0004] Catheters and other elongated medical devices (EMDs) are used in minimally invasive medical procedures to diagnose and treat various conditions of the vascular system, including neurovascular intervention (NVI), also known as neurointerventional procedures, percutaneous coronary intervention (PCI), and peripheral vascular intervention (PVI). These procedures typically involve the passage of a guidewire through the vasculature and the advancement of a catheter over the guidewire to deliver treatment. The catheterization procedure begins with the advancement of an introducer sheath into an appropriate vessel, such as an artery or vein, using standard percutaneous techniques. Through the introducer sheath, a sheath or guide 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 appropriate for the vasculature is then guided through the sheath or guide catheter to the target location in the vasculature. In some cases, such as in tortuous anatomy, a support catheter or microcatheter is inserted over the guidewire to assist in guiding the guidewire. A physician or operator can use an imaging system (e.g., a fluoroscope) to obtain a movie with contrast injection and select a fixed frame to use 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 is moving along the correct path to the target location. While visualizing the anatomy using fluoroscopy, the physician manipulates the proximal end of the guidewire or catheter to guide the distal tip into the appropriate vessel toward the lesion or target anatomical location and avoid advancing into branch vessels.

[0005] Robotic catheter-based surgical systems have been developed to assist physicians in performing catheterization 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 occlusions in the setting of acute ischemic stroke. During NVI procedures, physicians use a robotic system to control the operation of a neurovascular guidewire and microcatheter to gain access to the target lesion in order to provide treatment and restore normal blood flow. Target access is achieved by a sheath or guide catheter, but an intermediate catheter may also be required for more distal areas or to provide adequate support for the microcatheter and guidewire. Depending on the type of lesion and the treatment being treated, the distal tip of the guidewire is guided into or past the lesion. To treat an aneurysm, a microcatheter is advanced into the lesion, the guidewire is removed, and several embolic coils are deployed through the microcatheter into the aneurysm to block blood flow into the aneurysm. To treat an arteriovenous malformation, a liquid embolic agent is injected into the malformation via the microcatheter. Mechanical thrombectomy can be performed to treat vascular occlusions using aspiration and / or the use of a stent retriever. Depending on the location of the clot, aspiration can be performed through an aspiration catheter or, for smaller arteries, through a microcatheter. Once the aspiration catheter is at the site of the clot, negative pressure is applied to dislodge the clot through the catheter. Alternatively, the clot can be removed by deploying a stent retriever through the microcatheter. Once the clot is incorporated into the stent retriever, the clot is retrieved by retracting the stent retriever and microcatheter (or intermediate catheter) into the guiding catheter.

[0006] In PCI, physicians use a robotic system to gain access to the lesion by manipulating a coronary guidewire to deliver treatment and restore normal blood flow. Access is achieved by placing a guide catheter into the coronary artery ostium. The distal tip of the guidewire is guided through the lesion, and for complex anatomy, a microcatheter may 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 prior to stent implantation, either by delivering a balloon to pre-dilate the lesion, or by performing an atherectomy using, for example, a laser or rotational atherectomy catheter and a balloon over the guidewire. Diagnostic imaging and physiologic measurements can be performed using an imaging catheter or fractional flow reserve (FFR) measurements to determine appropriate therapy.

[0007] In percutaneous vascular intubation (PVI), physicians use a robotic system to deliver treatment and restore blood flow using techniques similar to those used in nonpercutaneous vascular intubation (NVI). The distal tip of a guidewire is guided through the lesion, and a microcatheter can be used to provide adequate support for the guidewire in complex anatomy. Blood flow is restored by delivering and deploying a stent or balloon into the lesion. Similar to PCI, lesion preparation and diagnostic imaging are also used.

[0008] Over-the-wire (OTW) catheters or coaxial systems are used when support at the distal end of a catheter or guidewire is required, for example, to navigate tortuous or calcified vasculature, reach distal anatomy, or traverse hard lesions. OTW catheters have an inner lumen for a guidewire that extends the full length of the catheter. This provides a relatively stable system because the guidewire is supported along its entire length. However, compared to rapid-exchange catheters (see below), this system has some disadvantages, including higher friction and a longer overall length. Typically, to remove or replace an OTW catheter while maintaining the position of the indwelling guidewire, the exposed length of the guidewire (external to the patient) must be longer than that of the OTW catheter. A 300-cm guidewire is generally sufficient for this purpose and is often referred to as an exchange-length guidewire. Due to the length of the guidewire, two operators are required to remove or replace an OTW catheter. This becomes even more challenging when using a triple coaxial, known in the art as a triaxial system (quadruple coaxial catheters are also known). However, due to their stability, OTW systems are frequently used in both NVI and PVI procedures. PCI procedures, on the other hand, typically utilize rapid-exchange (or monorail) catheters. The guidewire lumen in a rapid-exchange catheter passes only through the distal segment of the catheter, referred to as the monorail or rapid-exchange (RX) segment. With an RX system, the operator manipulates interventional devices parallel to one another (as opposed to an 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. Rapid-exchange length guidewires are typically 180-200 cm long. Given the shorter guidewire length and monorail, RX catheters can be changed by a single operator. However, when more distal support is required, RX catheters are often insufficient. Summary of the Invention

[0009] According to an embodiment, a data capture system for generating a profile using captured 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); a sensor system that captures parameters associated with the input from the reference operator; and a processing unit that uses the captured parameters to generate at least one profile associated with characteristics of the reference operator.

[0010] In one example, the parameter detected by the sensor includes at least one of a motion parameter or a load parameter.

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

[0012] In one example, the parameters detected by the sensor 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 and linear force; or (d) a combination of angular displacement and / or angular velocity and / or angular acceleration and torque.

[0013] In one example, the parameter detected by the sensor includes a manipulation frequency of the EMD.

[0014] In one example, the parameter detected by the sensor includes a combination of two or more of a motion parameter, a load parameter, position, displacement, frequency, linear velocity, linear force, rotational speed, or rotational torque.

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

[0016] In one example, the sensor system includes contact and / or non-contact sensors to detect 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 the 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 physician 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 physician metadata and case metadata.

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

[0024] In one example, the processing unit utilizes algorithmic analysis of input from one or more operators in forming the profile.

[0025] In one example, the processing unit will generate a power profile associated with the operator's profile that includes motion and load parameters.

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

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

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

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

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

[0031] In one example, the motion profile is constructed based on load parameters of 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 the doctor metadata and the case metadata.

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

[0035] In one example, the generated profile is updated with additional captured data from additional additional operators.

[0036] In one example, the processing unit updates the profile when new input data is available, such as after consecutive surgeries that are ongoing.

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

[0038] In one example, the processing unit can generate or update the profile and convert data into action rules offline or in real time.

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

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

[0041] In one example, the feedback is provided during a live procedure performed by the second operator.

[0042] In one example, the second operator can 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 operational control equations or constraints applied to the EMD or procedure, surgical recommendations, motion profiles, or general rule-based motions and loads.

[0045] In another embodiment, a robotic medical system includes: a module for independently and collaboratively actuating one or more EMDs; a user interface that receives input from a reference operator to manipulate the EMD; a sensor system to detect motion and / or load parameters applied to the EMD; a data capture portion that captures parameters detected by the sensor associated with the input from the reference operator, the captured parameters including at least one motion or load parameter, wherein the data capture portion associates the captured parameters with characteristics of the reference operator; and a processing unit that converts the detected parameters into operational control equations for the slender medical device and surgery.

[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 operation commands for the robotic device; and generating a profile using the captured input parameters, the profile being 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 operation commands for the robotic device; and generating a profile using the captured input parameters, the profile being 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 apparatus, the captured input parameters including at least one motion or load parameter; converting the captured input parameters into operation commands for the robotic apparatus; and generating a profile using the captured input parameters, the profile being 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 a slender medical device, the user interface including sensors to detect parameters associated with the input from the reference operator; a recording portion that captures parameters associated with the input from the reference operator detected by the sensors, the captured parameters including at least one motion or load parameter; and a processing unit that generates parameters for adaptive guidance of operation of the slender 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 capture portion that captures parameters associated with the input from the reference operator detected by the sensor; a processing unit that converts the input from the operator into operational adaptive guidance for a slender medical device and surgery; and at least one module that independently and collaboratively actuates one or more EMDs.

[0051] In another embodiment, a method includes: capturing input parameters from a reference operator of a slender medical device, the captured input parameters including at least one motion or load parameter; converting the captured input parameters into operation commands for the slender medical device; and generating guidance parameters for the slender 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 operational 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 operation 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 captured 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 sensor 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 captured 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 a combination of two or more of a motion parameter, a load parameter, position, displacement, frequency, linear velocity, linear force, rotational velocity, or rotational torque. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The present invention will be more fully understood from the following detailed description taken in conjunction with the accompanying drawings, wherein like parts are designated by reference numerals and wherein: Figure 1 is a perspective view of an exemplary catheter-based surgical system according to an embodiment; Figure 2 is a schematic block diagram of an exemplary catheter-based surgical system according to an embodiment; Figure 3 is a perspective view of a robotic actuator for a catheter-based surgical system according to an embodiment; Figure 4 is a schematic diagram of an exemplary data capture system for use with a robotic medical system having an elongated medical device (EMD), according to an embodiment; Figure 5 is a schematic diagram of an exemplary robotic medical system with an exemplary data capture system according to an embodiment; Figure 6is a flow chart illustrating an exemplary method for generating a profile associated with operator characteristics using operator input according to an embodiment; Figure 7 is a flow chart illustrating an exemplary method for generating adaptive guidance parameters using operator input according to an embodiment; Figure 8 illustrates an exemplary data input arrangement and data utilization of a robotic medical system with an EMD according to an embodiment; Figure 9 illustrates exemplary actuator / sensor arrangements for use with various EMDs, according to embodiments; Figure 10 illustrates an exemplary data capture linear module for use with various EMDs, according to an embodiment; and Figure 11 Illustrated is an exemplary data capture rotation module for use with various EMDs, according to an embodiment. DETAILED DESCRIPTION

[0057] Figure 1 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 treating STEMI), neurovascular intervention (NVI) (e.g., for treating emergency large vessel occlusion (ELVO)), peripheral vascular intervention (PVI) (e.g., for treating critical limb ischemia (CLI)), etc. Catheter-based medical procedures may include diagnostic catheterization procedures, during which one or more catheters or other elongated medical devices (EMDs) are used to help diagnose a patient's condition. For example, during one embodiment of a catheter-based diagnostic procedure, a contrast agent is injected into one or more arteries via a catheter, and images of the patient's vasculature are captured. 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. This can be achieved through the use of adjuncts such as intravascular ultrasound (IVUS), optical coherence tomography (OCT), fractional flow reserve (FFR), and other devices54 ( Figure 2 ) to enhance therapeutic procedures. However, it should be noted that those skilled in the art will recognize that certain specific percutaneous interventional devices or components (e.g., type of guidewire, type of catheter, etc.) may be selected based on the type of procedure to be performed. The catheter-based surgical system 10 may perform any number of catheter-based medical procedures with minor adjustments to accommodate the specific percutaneous interventional device to be used in the procedure.

[0058] The catheter-based surgical system 10 includes, among other components, a bedside unit 20 and a control station 26. The bedside unit 20 includes a robotic 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 robotic actuator 24. The positioning system 22 may be, for example, a robotic arm, an articulated arm, a holder, or the like. One end of the positioning system 22 may be attached to, for example, a track, a base, or a cart on the patient table 18. The other end of the positioning system 22 is attached to the robotic actuator 24. The positioning system 22 (along with the robotic actuator 24) can be removed 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 orient the robotic actuator 24 relative to the patient 12 for surgical procedures. In one embodiment, the patient table 18 is operably supported by a support 17 secured to a floor and / or ground. The patient table 18 is capable of moving relative to the support 17 in multiple degrees of freedom, such as roll, pitch, and yaw. The bedside unit 20 may also include a control device and display 46 ( Figure 2 For example, the control device and display may be located on the housing of the robot drive 24.

[0059] Typically, the robotic driver 24 may be equipped with appropriate percutaneous access devices and accessories 48 ( Figure 2 ) (e.g., guidewires, various types of catheters including balloon catheters, stent delivery systems, stent retrievers, embolic coils, liquid embolic agents, aspiration pumps, devices for delivering contrast agents, medications, hemostatic valve adapters, syringes, stopcocks, inflation devices, etc.) to allow a user or operator 11 to perform catheter-based medical procedures via the robotic system by operating various control devices such as the control devices and inputs located at the control station 26. The bedside unit 20, and in particular the robotic drive 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 the 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 the bedside unit 20 is referred to as the bedside unit user or bedside unit operator. The robotic drive 24 includes a device mounted to a track or linear member 60 ( Figure 3 1 . A plurality of device modules 32a-d are provided (shown in FIG. 1 ). 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 a guidewire. For example, a robotic actuator 24 can be used to automatically advance a guidewire into a diagnostic catheter and into a guide catheter in an artery of patient 12. One or more devices, such as EMDs, are introduced into the body (e.g., a blood vessel) of patient 12 at insertion point 16, for example, via an introducer sheath.

[0060] The bedside unit 20 is in communication with the control station 26, thereby allowing signals generated by user inputs to the control station 26 to be transmitted wirelessly or via hardwire to the bedside unit 20 to control various functions of the bedside unit 20. As described below, the control station 26 may include a control computing system 34 ( Figure 2 ) or coupled to the bedside unit 20 via the control computing system 34. The bedside unit 20 may also provide communication to the control station 26, the control computing system 34 ( Figure 2 ) or both provide feedback signals (e.g., load, speed, operating status, warning signals, error codes, etc.). Communication between the control computing system 34 and the various components of the catheter-based surgical system 10 may be provided via a communication link, which may be a wireless connection, a cable connection, or any other means capable of allowing communication between the components. The control station 26 or other similar control system may be located at a local location (e.g., Figure 2 ) or at a remote location (e.g., Figure 2 ). The catheter surgery system 10 can be operated by a control station at a local site, a control station at a remote site, or both the local and remote control stations. At the local site, the user or operator 11 and the control station 26 are located in the same room as the patient 12 and the bedside unit 20 or in an adjacent room. As used herein, the local site is the location of the bedside unit 20 and the patient 12 or object (e.g., an animal or a cadaver), and the remote site 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 the controlling computing system) at the remote site and the bedside unit 20 and / or the controlling computing system at the local site can communicate with each other via the Internet using communication systems and services 36 ( Figure 2 In one embodiment, the remote site and the local (patient) site are located remotely from one another, e.g., in different rooms in the same building, different buildings in the same city, different cities, or other different locations where the remote site does not have physical access to the bedside unit 20 and / or the patient 12 at the local site.

[0061] The 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, the control station 26 allows the user or operator 11 to control the bedside unit 20 to perform a catheter-based medical procedure. For example, the input module 28 can be configured to cause the bedside unit 20 to use a percutaneous interventional device (e.g., an EMD) interfaced with the robotic actuator 24 to perform various tasks (e.g., to advance, retract, or rotate a guidewire, advance, retract, or rotate a catheter, inflate or deflate a balloon located on a catheter, position and / or deploy a stent, position and / or deploy a stent retriever, position and / or deploy a coil, inject contrast media into a catheter, inject a liquid embolic agent into a catheter, inject medication or saline into a catheter, apply suction to a catheter, or perform any other function that may be performed as part of a catheter-based medical procedure). The robotic actuator 24 includes various drive mechanisms to cause movement (e.g., axial and rotational movement) of components of the bedside unit 20, including the percutaneous interventional device.

[0062] In one embodiment, the input module 28 may include one or more touch screens, joysticks, scroll wheels, and / or buttons. In addition to the input module 28, the control station 26 may use additional user controls 44 ( Figure 2), such as a foot switch and a microphone for voice commands. The input module 28 can be configured to advance, retract, or rotate various components and percutaneous interventional devices, such as a guidewire, and one or more catheters or microcatheters. For example, the buttons may include an emergency stop button, a multiplier button, a device selection button, and an automatic movement button. When the emergency stop button is pressed, the power (e.g., electrical power) to the bedside unit 20 is turned off or removed. When 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 the input module 28. When in position control mode, the multiplier button changes the mapping between the input distance and the output command distance. The device selection button allows the user or operator 11 to select which percutaneous interventional devices loaded into the robotic drive 24 are controlled by the input module 28. The automatic movement button is used to enable algorithmic movement that the catheter-based surgical system 10 can perform on the percutaneous interventional devices without direct commands from the user or operator 11. In one embodiment, input module 28 may include one or more controls or icons (not shown) displayed on a touch screen (which may or may not be part of display 30) that, when activated, cause operation of a component of catheter-based surgery system 10. Input module 28 may also include a balloon or stent control device 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, touch screens, etc., which may be used to control one or more specific components dedicated to that control device. In addition, one or more touch screens may display one or more icons (not shown) related to various portions of input module 28 or various components of catheter-based surgery system 10.

[0063] The control station 26 may include a display 30. In other embodiments, the control station 26 may include two or more displays 30. The display 30 may be configured to display information or patient-specific data to a user or operator 11 located at the control station 26. For example, the 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.). In addition, the display 30 may be configured to display procedure-specific information (e.g., procedure checklist, recommendations, procedure duration, catheter or guidewire position, amount of medication or contrast agent delivered, etc.). In addition, the display 30 may be configured to display information to provide information related to the control computing system 34 ( Figure 2 The display 30 may include touch screen capabilities to provide some user input capabilities for the system.

[0064] The catheter-based surgical system 10 also includes an imaging system 14. The imaging system 14 can be any medical imaging system that can be used in conjunction with a catheter-based medical procedure (e.g., non-digital X-ray, digital X-ray, CT, MRI, ultrasound, etc.). 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 can include a C-arm ( Figure 1 ), the C-arm allows the imaging system 14 to be rotated partially or completely around the patient 12 to obtain images at different angular positions relative to the patient 12 (e.g., sagittal view, caudal view, anteroposterior view, etc.). In one embodiment, the imaging system 14 is a fluoroscopy system that includes a C-arm having an X-ray source 13 and a detector 15, also referred to as an image intensifier.

[0065] The imaging system 14 can be configured to capture X-ray images of appropriate areas of the patient 12 during a procedure. For example, the imaging system 14 can be configured to capture one or more X-ray images of the head to diagnose neurovascular conditions. The imaging system 14 can also be configured to capture one or more X-ray images (e.g., real-time images) during a catheter-based medical procedure to assist the user or operator 11 at the control station 26 in properly positioning a guidewire, guide catheter, microcatheter, stent retriever, coil, stent, balloon, etc. during the procedure. The one or more images can be displayed on the display 30. For example, the images can be displayed on the display 30 to allow the user or operator 11 to accurately move the guide catheter or guidewire into position.

[0066] To clarify orientation, a rectangular coordinate system with X, Y, and Z axes is introduced. The positive X axis is oriented in the longitudinal (axial) distal direction, that is, from the proximal end to the distal end, or 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 upward, that is, in the direction opposite to gravity, and the Y axis is automatically determined by the right-hand rule.

[0067] Figure 2 is a block diagram of a catheter-based surgical system 10 according to an exemplary embodiment. The catheter surgical system 10 may include a control computing system 34. For example, the control computing system 34 may be physically located at the control station 26 ( Figure 1). The control computing system 34 may generally be an electronic control unit suitable for providing the various functionalities described herein for the catheter-based surgical system 10. For example, the control computing system 34 may be an embedded system, dedicated circuitry, a general-purpose system programmed with the functionalities described herein, or the like. The control computing system 34 communicates with the bedside unit 20, communication systems and services 36 (e.g., the internet, a firewall, a cloud service, a session manager, a hospital network, etc.), a local control station 38, additional communication systems 40 (e.g., a telepresence system), a remote control station and computing system 42, and patient sensors 56 (e.g., an electrocardiogram (ECG) device, an electroencephalogram (EEG) device, a blood pressure monitor, a temperature monitor, a heart rate monitor, a respiratory monitor, etc.). The control computing system also communicates with the imaging system 14, the patient table 18, additional medical systems 50, a contrast agent injection system 52, and accessory devices 54 (e.g., IVUS, OCT, FFR, etc.). The bedside unit 20 includes a robotic drive 24, a positioning system 22, and may include additional control devices and a display 46. As described above, additional controls and displays may be located on the housing of the robotic drive 24. Interventional devices and accessories 48 (e.g., guidewires, catheters, etc.) interface with the bedside system 20. In one embodiment, the interventional devices and accessories 48 may include specialized devices (e.g., IVUS catheters, OCT catheters, FFR wires, diagnostic catheters for angiography, etc.) that interface with their respective accessory devices 54, i.e., IVUS systems, OCT systems, and FFR systems, etc.

[0068] In various embodiments, the control computing system 34 is configured to control the computer system 34 based on the user's interaction with the input module 28 (eg, the control station 26 ( Figure 1, such as an input module of a local control station 38 or a remote control station 42) and / or generates control signals based on information accessible to the control computing system 34 so that a medical procedure can be performed using the catheter-based surgical system 10. The 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 similar components to the local control station 38. The remote control station 42 and the local control station 38 may be different and customized based on their desired functionality. The additional user control device 44 may include, for example, one or more foot input controls. The foot input controls may be configured to allow a user to select functions of the imaging system 14, such as turning X-ray on and off and scrolling through different stored images. In another embodiment, the foot input device may be configured to allow a user to select which devices are mapped to a scroll wheel included in the input module 28. Additional communication systems 40 (eg, audio conferencing, video conferencing, telepresence, etc.) may be employed to help the operator interact with the patient, medical personnel (eg, angio-suite staff), and / or equipment near the bedside.

[0069] The catheter-based surgical system 10 may be connected 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 expansion system, a drug injection system, a drug tracking and / or recording system, a user log, an encryption system, a system for limiting access to or use of the catheter-based surgical system 10, and the like.

[0070] As mentioned, the control computing system 34 communicates with the bedside unit 20, which includes the robotic drive 24, the positioning system 22, and may include additional controls and a display 46, and may 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 robotic drive 24. Figure 3 is a perspective view of a robotic actuator for a catheter-based surgical system 10 according to an embodiment. Figure 3In , the robotic drive 24 includes a plurality of device modules 32a-d coupled to the linear member 60. Each device module 32a-d is coupled to the linear member 60 via a stage 62a-d that is movably mounted to the linear member 60. The device modules 32a-d can be connected to the stages 62a-d using connectors such as offset 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 the corresponding device modules 32a-d coupled to the stages 62a-d) can move independently relative to each other and the linear member 60. A drive mechanism is used to actuate each stage 62a-d. In Figure 3 In the embodiment shown in , the drive mechanism includes an independent stage translation motor 64a-d and a platform drive mechanism 76 coupled to each stage 62a-d, for example, 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 motors 64a-d themselves may be linear motors. 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 may be rotated and each stage 62a-d may engage and disengage the lead screw to move, for example, advance or retract. In Figure 3 In the embodiment shown in FIG, the stages 62a-d and device modules 32a-d are in a serial drive configuration.

[0071] Each device module 32a-d includes a drive module 68a-d and a cartridge 66a-d mounted on and coupled to the drive module 68a-d. Figure 3In the embodiment shown in FIG, each box 66a-d is mounted to the drive module 68a-d in a vertical orientation. In other embodiments, each box 66a-d can be mounted to the drive module 68a-d in other mounting orientations. Each box 66a-d is configured to interface with and support the proximal portion of the EMD (not shown). In addition, each box 66a-d may include an element that provides one or more degrees of freedom in addition to the linear motion provided by the actuation of the corresponding stage 62a-d for linear movement along the linear member 60. For example, the box 66a-d may include an element that can be used to rotate the EMD when the box 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 box 66a-d to provide additional degrees of freedom. Each box 66a-d also includes a channel in which a device support 79a-d is located, and each device support 79a-d is used to prevent the EMD from buckling. Support arms 77a, 77b, and 77c are attached to each device module 32a, 32b, and 32c, respectively, to provide a fixing point for supporting the proximal ends of device supports 79b, 79c, and 79d, respectively. The robotic drive 24 may also include a device support connector 72 connected to the device support 79, the distal support arm 70, and a support arm 770. The support arm 770 is used to provide a fixing point to support the proximal end of the distal-most device support 79a housed in the distal-most device module 32a. In addition, an introducer interface support (redirector) 74 may be connected to the device support connector 72 and the EMD (e.g., an introducer sheath). The configuration of the robotic drive 24 has the following advantages: the size and weight of the driving robotic drive 24 can be reduced by using an actuator on a single linear member.

[0072] To prevent pathogens from contaminating the patient, the medical staff receives the patient 12 or the subject 12 from the bedside unit 20. Figure 1 Aseptic technique is used in a room (shown in ). The room that houses the bedside unit 20 and the patient 12 can be, for example, a catheterization laboratory or a vascular laboratory. Aseptic technique includes the use of sterile barriers, sterile equipment, appropriate patient preparation, environmental controls, and contact guidelines. Therefore, all EMDs and interventional accessories are sterile and can only come into contact with sterile barriers or sterile equipment. In one embodiment, a sterile drape (not shown) is placed over the non-sterile robotic drive 24. Each cassette 66a-d is sterile and serves as a sterile interface between the drape-covered robotic drive 24 and at least one EMD. Each cassette 66a-d can be designed to be sterilized for a single use, or to be resterilized in whole or in part, so that the cassette 66a-d or its components can be used in multiple procedures.

[0073] In one example, various types of data during a procedure performed by an operator can be captured and used to generate profiles associated with various characteristics. The various types of data are associated with input 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 that can then be used to facilitate operation of the robotic medical system by the same or a different operator.

[0074] In another example, the captured data can be used to provide adaptive guidance by the same or a different operator during training, simulation, or live surgery. As described in various examples below, the guidance parameters can include limitations on the operation or other guidance of the robotic medical system.

[0075] definition 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 ) and applying various mappings and transformations, such as filters, Fourier transforms, and other mathematical or numerical mappings and transformations, 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 limits, successful and unsuccessful attempts (e.g., number of attempts to select a branch), total travel of each EMD, and other such parameters are examples of parameters captured during a case or data capture event. Additionally, additional data regarding operator characteristics and the surgery (case) can be used to better represent, describe, categorize, or segment the data. This latter data is often referred to as metadata.

[0076] In various examples, a profile may include a collection of data associated with a user or user group. This data may be a collection of metadata, collected kinematic or dynamic (or motion or load) parameters, or parameters derived from an algorithm that processes metadata and kinematic or dynamic parameters. Kinematic parameters refer to mathematical representations of a point, body, or system of body motion, such as displacement, velocity, acceleration, time, frequency (frequency = 1 / time), and trajectory. This does not take into account the load required to move the device. Dynamic parameters refer to mathematical representations of a point, body, or system of body motion, such as displacement, velocity, acceleration, time, frequency (frequency = 1 / time), and trajectory, that take into account the load required to move the device and the external loads (or losses) experienced by the device or manipulator that moves the device. Profiles related to robotic EMD drive systems may include relevant force zones (typical, high, maximum), which are further categorized by procedure type, device type being driven, device location within the anatomy, etc., velocity thresholds or limits, load thresholds or limits, power thresholds or limits, or typical device used (device length).

[0077] In some examples, operator-associated data, referred to 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 / procedures used (e.g., use of aspiration or stent retriever during mechanical thrombectomy), preferred device (e.g., conventional guide catheter or sheath versus balloon guide catheter), risk tolerance, and patient population acuity.

[0078] The subset of metadata representing data that can be collected from a medical procedure or training case is referred to as case metadata. Examples of case metadata may include, but are not limited to, procedure length (time), subsets or distinct use cases performed within the procedure, procedure date, devices used, treatment technique / procedure sequence, patient age, case type, treatment location, access location (femoral, radial, carotid, etc.), contrast used, radiation delivered (fluoroscopy time), images captured (e.g., real-time and reference fluorescence images), robotic manipulation time, robotic device loading time, robot setup time, robot movement, payload, outcomes before, during, and after treatment, and clinical evaluation metrics.

[0079] As used herein, the term "motion parameter" refers to a kinematic parameter and includes translational and rotational displacement, velocity, acceleration, and the time history of these parameters (i.e., displacement (t), velocity (t), acceleration (t)), as well as any function of these parameters, such as the frequency of displacement, velocity, and acceleration. Motion parameters can be integrated or differentiated with respect to time to obtain other motion 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.

[0080] In various examples, the data capture system includes a sensor system and a data acquisition system, wherein the sensor system includes sensors to detect motion and / or load parameters, and the data acquisition system records and / or displays the output of the sensors. The data acquisition system may be equipped with a reference timing unit to record the time associated with each data point. In addition, it may also be equipped with a signal conditioning unit to filter and amplify the signal. The sensor system may include a motion sensor and a load sensor. The motion sensor is a sensor that detects motion parameters. Contact motion sensors include but are not limited to accelerometers, LVDTs, and encoders that are directly or indirectly connected to the EMD. Non-contact motion sensors include but are not limited to CMOS sensors, optical encoders, ultrasonic sensors, standard or high-speed cameras. Load sensors are sensors that measure force and / or torque.

[0081] In various examples, the data capture system can capture motion parameters. Motion parameters are equivalent to kinematic parameters and include linear and rotational displacement, velocity, acceleration, and the time history 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 frequency of displacement, velocity, and acceleration. The data capture system captures the motion parameters over time so that the time history of each of these parameters is also captured. The motion parameters can be integrated or differentiated with respect to time to obtain other motion 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.

[0082] The data capture system is capable of capturing load parameters, including force and torque parameters and the time history of these parameters (i.e., force(t) and torque(t). The data capture system captures the load parameters over time such that the time history of each of these parameters is captured.

[0083] In one example, a data capture system can simultaneously capture applied force (e(t)) and flow (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 terms, 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 the model used to describe power flow within multi-domain systems (usually represented by a bond diagram) can also include resistance (R), inertia (I), and compliance (C) components. For linear mechanical systems, the applied force is force, and the flow is velocity. For angular mechanical systems, the applied force is torque, and the flow is angular velocity. For electromagnetic systems, the applied force is voltage, and the flow is current.

[0084] The target operator, or reference operator, for data capture systems and medical robotic systems is an individual experienced in performing medical procedures, such as an interventionalist, radiologist, or surgeon. However, for comparative purposes, data related to other types of operators may be captured. Furthermore, a reference operator may be the individual from whom the data was captured. Reference operators may include, but are not limited to, experienced physicians familiar with vascular interventions.

[0085] 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, which are referred to in the literature as techniques such as synchronized motion (e.g., drilling techniques). A master profile can be formed using any combination of smaller profiles such as motion profiles, power profiles, load profiles, case metadata, and physician profiles.

[0086] In some examples, the captured data can be used to provide adaptive guidance during training, simulation, or live procedures 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 override certain guidance but not certain other 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 a combination of motions for certain situations.

[0087] The term "adaptive guidance" refers to the proactive and responsive guidance provided to the operator during a procedure. It can be used during training, simulation, or live surgery by the same or a different operator. The content and type of guidance may be updated over time as the operator gains more experience, or as devices improve and new technologies become available. The guidance provided to the operator by the system may include limitations and rules within the context of the procedure being performed. The operator may be able to override some guidance without overriding others, such as certain limitations or rules. Examples include operational limitations (e.g., load, speed, displacement, etc.) or the sequence of steps, or the device used, or a combination of movements for certain situations.

[0088] Data capture system Various examples can be found in Figure 4 The exemplary system may be a standalone system or may be implemented as part of a robotic medical system, such as that described above with reference to Figure 1-3 The system 10 is described. For example, Figure 4 The exemplary system 100 may be implemented as part of the bedside unit 20 , the control station 26 , and / or the control computing system 34 of the system 10 .

[0089] Figure 4 The data capture system 120 includes a sensor system 122 and a processing unit 124. Figure 5 As shown in the example of , the data capture system 120 may also include a device (EMD) interface 110. Various examples of the EMD interface 110, the sensor system 122, and the processing unit 124 are described in further detail below.

[0090] EMD interface The exemplary system 100 includes an EMD interface 110 to receive input from an operator, such as a practitioner, via an input module 220. Figure 5 As described above, the input module 220 may include various types of input devices, such as a joystick or other tactile input device. The EMD interface 110 operates 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 drive 24, and the input module 220 may be the same as described above with reference to FIG. Figure 1-3 1. A portion of the control station 26 of the exemplary system 10 is depicted. Various examples of the EMD interface 110 are described in further detail below.

[0091] 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 described above with reference to Figure 1-3 The depicted bedside unit 20 is, or is a portion of, the bedside unit 20. For example, the robotic EMD may include a robotic drive 24 of the bedside unit 20.

[0092] As described above, the data capture system 120 of the exemplary system 100 may be implemented in a robotic medical system. In various examples, the data capture system 120 may be implemented within various parts of the robotic medical system. For example, in Figure 1-3 In the exemplary system 10 of FIG. 1 , certain portions of the data capture system 120 may be provided in the control station 26, the bedside unit 20 (e.g., within the robotic drive 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.

[0093] In one example, if Figure 5As shown in FIG, a 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 the loads and motion parameters applied to an EMD during a robotic vascular intervention procedure. The robotic system 200 includes an input module 28 for receiving motion commands for the EMD from an operator. In this regard, mechanical input from the operator (e.g., movement of a control device) is coupled and transmitted to corresponding outputs or commands (e.g., movement of a catheter). In another example, the input module 28 receives digital input from the operator to actuate the EMD accordingly. In this regard, the input from the operator may be received as or converted into digital signals. These signals may be transmitted, for example, via the control computing system 34 of the robotic system 200. The robotic actuator 24 of the medical robotic 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 for detecting the loads and motion parameters applied to the EMD actuated by the robotic actuator 24. The data capture system 120 also includes a processing unit (processing unit 124) to record and post-process the captured data. The processing unit 124 processes the captured data and combines it with case metadata and physician metadata to generate an operator profile. The processing unit 124 can further process the profile to generate operating rules / limits. The robotic system 200 can use the newly generated rules / limits to update existing operating rules / limits defined for the robotic system 200. The robotic system 200 allows the operator to override operating rules / limits by entering numerical values ​​for characteristic parameters and / or by applying physical / mechanical inputs to the EMD interface coupled to the data capture system 110.

[0094] Sensor system like Figure 4 As shown in the example of , 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 fixture that interfaces 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 locations and operate at different times. Various types of sensors may be provided to detect various parameters. For example, sensors may be provided to detect motion (e.g., linear displacement, linear velocity, linear acceleration, rotational displacement, rotational velocity, or rotational acceleration) or load (e.g., linear force or rotational torque). For example, the various sensors may be capable of detecting other parameters, such as the frequency of the input.

[0095] In one example, sensor system 122 is provided to capture motion and loading parameters of the EMD while the EMD is being directly manipulated by an operator. Thus, sensor system 122 can detect operator-applied forces or torques or operator-induced motion parameters (e.g., displacement, velocity, acceleration). In other examples, the parameters detected by sensor system 122 can be related to the EMD's response to operator input. For example, sensor system 122 can detect displacement, velocity, acceleration, or reactive load of the catheter in response to operator input.

[0096] Any of a variety of sensors may be provided within sensor system 122. For example, sensor system 122 may include contact sensors and / or contactless (or non-contact) 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, directly or indirectly connected to an 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, optical-based load sensors, or magnetic-based load sensors. In one example, sensor system 122 may condition the signals from the sensors to facilitate their 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 the signals from the various sensors. In another example, the signal conditioning unit may be equipped with a low-pass filter and / or amplifier to filter out high-frequency noise and amplify the signals, respectively.

[0097] The data captured by sensor system 122 may be stored for processing by processing unit 124 or another processor. In this regard, the data may be stored on a storage device of data capture system 120 or on an external storage device independent of data capture system 120. The stored data may be retrieved from the storage device when needed.

[0098] In one example, the data capture system includes a timing unit, such as a hardware clock source, that reports the time associated with each data point. Sensor data points are stored along with their corresponding time. In one example, 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 can be used for further processing. Further processing of the data can reveal secondary parameters that are not directly measured. For example, the frequency of displacement, velocity, and acceleration can be determined from the time history of these parameters. As another example, velocity can be determined by differentiating the 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. The sampling rate can be adjusted based on the frequency of the sensed parameter.

[0099] The sensor system 122 may include any of a variety of sensors to capture the desired parameters associated with the user input. The sensor system 122 is provided to accurately capture and record the dynamic motions and loads that the physician will use when manipulating the device proximally. In this regard, the primary measurements are force, torque and its rate of change, displacement, linear velocity and acceleration, and rotational velocity and acceleration.

[0100] In one example, force measurement can be achieved using a sensor system comprising a force sensor and a mechanical fixture that interfaces with an EMD. The bottom of the force sensor is fixed to a substrate (ground). The mechanical fixture is attached to the force sensor to provide a friction 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 that is desired to be captured. For example, the friction 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 a design, two rows of locating pins can serve as guides for the EMD to provide support. The mechanical fixture used as the interface to the EMD is designed to apply an adjustable resistive load to the EMD as the operator manipulates the EMD, and to sense and store load and motion parameters. The operator can adjust the resistive load to simulate different load and motion scenarios that would occur in actual vascular intervention situations, such as in non-manual surgery.

[0101] In one example, the measurement of torque can be achieved by using one or more modules to measure the torque on the EMD that can be twisted. Like the force measurement module, the torque measurement module includes an interface and a sensor. The sensor can directly measure the torque or convert the reaction force into torque. A torque sensor is provided to allow the EMD to rotate continuously when an adjustable torque resistance is applied to it, or to simulate the EMD with a certain compliance when the far end is fixed due to high torque resistance or being stuck by something. In another embodiment, the motor or actuator current can be used to calculate the load applied to the EMD.

[0102] File Generation As described above, the use of the robotic medical system by one or more operators can be used to 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 the parameters captured by the sensor system 122 to facilitate 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 characteristics of the operator (doctor metadata) and / or associate the profile with characteristics of the case (case metadata). Figure 4 As shown in , profiles along with their associations with various parameters may be stored in profile module 130. Profiles may be used to facilitate operation of various devices for training, simulation, or live surgery via a training system, simulator, or robotic medical system, respectively.

[0103] Figure 6 A method for generating and associating profiles is illustrated in FIG. In exemplary method 300 , parameters associated with user inputs are captured by sensor system 122 , such as data capture system 120 (block 310 ). The captured parameters can be associated with any one or a combination of a variety of inputs. In one example, the parameters are associated with discrete user inputs, which can be any type of motion or load parameter. For example, the captured parameters can be associated with discrete linear velocity, linear force, rotational velocity, or rotational torque. In one specific example, the captured parameters can be associated with each of six spatial velocity and six spatial force / torque inputs. Thus, sensor system 122 can separate the measurements into different modules that can be positioned on a tabletop. As in a clinical setting, the physician can operate while standing at the tabletop, with each sensor module positioned relative to the patient. Sensor data can be collected at the proximal end of the EMD, where the EMD is being manipulated by the operator.

[0104] In another example, the captured parameters can be associated with various combinations of user inputs. In one specific example, the captured parameters are associated with a combination of linear speed and rotational speed (e.g., a drilling motion), a combination of linear force and rotational torque, a combination of linear speed and linear force, and / or a combination of rotational speed and rotational torque. When capturing a combination of load and speed, a new product parameter can be determined, such as a power parameter as the product of load and speed. In various examples, the various parameters of the combination are measured simultaneously.

[0105] In yet another example, the captured parameters may be associated with any number of combinations of user inputs. For example, the captured parameters may be associated with any combination of linear motion, linear load, rotational motion, and / or rotational load.

[0106] In one example, the data capture system 120 captures parameters from a single EMD. In this case, one or more EMDs may be nested / assembled to represent the actual configuration of the EMDs during an actual procedure, but the motion and load parameters are captured from a single EMD. In another example, more than one EMD is nested / assembled, and the sensor system 122 uses sensors to capture concurrent data from the more than one EMD. By way of example, the data capture system captures the relative motion (referred to as differential motion) of two or more EMDs and / or the relative loads, such as differential forces and torques, of two or more EMDs.

[0107] Reference again Figure 6 In the exemplary method 300, the captured parameters are converted into at least one profile (block 320). In one example, the processing unit 124 may generate the profile based on the captured data associated with a single reference operator. In this regard, the profile may be based on a single or multiple procedures performed by the reference operator. The profile may be updated or modified with each subsequent procedure performed by the reference operator. In this regard, the processing unit 124 may utilize algorithmic analysis of input from one or more operators when generating the profile.

[0108] 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 using algorithmic analysis to combine data associated with multiple operators. 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 be weighted more heavily 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 by weighting operators with approximately n years of experience more heavily than operators 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, and so on. For a profile corresponding to 15 years of experience, an operator with 10 years of experience may be weighted more heavily than an operator with 5 years of experience. Similarly, weighting can be applied to provide profiles associated with any of a variety of operator characteristics. In one example, the profile is based on a combination of reference operator characteristics, patient characteristics, anatomical data, physiological data, intravascular device characteristics, procedure characteristics, technique characteristics, imaging data, and surgical results. The profile can be updated or generated by combining the 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) with successive procedures.

[0109] 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 in six dimensions (three linear and three rotational) throughout the procedure. In this regard, the profile may be a continuous profile for each point in the procedure, or may include discrete points at various stages of the procedure. In one example, the profile generated by processing unit 124 may be based on a heuristic model. The heuristic model may be based on data captured from one or more procedures.

[0110] Reference again Figure 6In the exemplary method 300 , the profile is associated with operator characteristics (block 330 ). In one example, the profile is associated with metadata about the operator. 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 procedure in which the data was captured. In this regard, the captured data may be associated with anatomy, patient characteristics, device specifications, procedure type, techniques used, or surgical outcomes. In other examples, the profile may be associated with metadata about the surgical case. For example, the case metadata may include anatomy, anatomical location, patient characteristics, device type, device specifications, procedure type, specific parts of the procedure, physician descriptions (e.g., name, age, number of cases per year, specialty, and experience), techniques used, or surgical outcomes.

[0111] Figure 6 The exemplary method 300 can be implemented on a computer or another electronic device. In addition, 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.

[0112] Adaptive Boot 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 assist an operator in using the robotic EMD, for example, for 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 that are associated with user input. Guidance parameters can be translated into limits on, for example, linear speed, linear force, rotational speed, rotational torque, or any of a variety of other parameters. In another example, adaptive guidance can be achieved through rules and relationships between more than one parameter. For example, a speed limit can be a function of the load acting on the EMD. In such an example, the maximum allowable speed can be reduced when the load is deemed high to enhance surgical safety. In one example, the limits are applied consistently throughout the entire procedure. In another example, the limits are applied variably throughout the procedure. 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 body, the surgical environment, the patient's age, the direction of movement of the EMD, or the load level applied by the operator.

[0113] Figure 7An exemplary method associated with adaptive guidance is illustrated in FIG. According to exemplary method 400, captured parameters associated with user input are received for processing (block 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 transmitted to a processor, such as processing unit 124.

[0114] according to Figure 7 In the exemplary method 400, the captured parameters are used to generate adaptive guidance parameters for use with the robotic medical device (block 420). In one example, the 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 define linear velocity limits based on the operator's experience level. In this regard, the guidance parameters may define stricter limits for less experienced operators and looser limits for more experienced operators. In other examples, the guidance parameters may define limits based on the patient's age. In this regard, the limits may be stricter for very young or very elderly patients.

[0115] Similarly, guidance parameters can be dependent on the stage of surgery. In one example, adaptive guidance parameters provide a constant level of guidance throughout the entire procedure. For example, adaptive guidance parameters can provide constant limits on various inputs (e.g., force, torque, linear velocity, or rotational speed) at each stage of the procedure. In other examples, these limits can vary throughout the procedure. For example, when approaching delicate anatomy, the limits on linear velocity may be tightened, while otherwise relaxed.

[0116] The adaptive guidance parameters may be used to facilitate the operator's operation of the robotic medical device (block 430). In this regard, alerts or other forms of guidance may be provided to the operator during the procedure based on the guidance parameters.

[0117] Furthermore, in various examples, the operator may be provided with the option of accepting or overriding the constraints defined by the guidance parameters. One or more constraints (eg, limits) may be sufficiently critical to not allow the option of being overridden, while other constraints may allow for operator discretion.

[0118] As described above, in some examples, the guidance parameters may be reflected as constraints. In other examples, the 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. The motion profile may include synchronized motion associated with input from an operator. Various profiles may be based on a database associated with the operator's input and may indicate synchronized motion patterns associated with one or more EMDs input from the operator.

[0119] In one example, adaptive guidance parameters can be modified or updated based on additional data associated with other practitioners, procedures, or patients. In one example, adaptive guidance parameters can be updated periodically or continuously (on an ongoing basis) with successive procedures. For example, restrictions on various operator inputs can be tightened or relaxed based on additional procedure data.

[0120] and Figure 6 As in the exemplary method 300, Figure 7 The exemplary method 400 can also be implemented on a computer or another electronic device. In addition, 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.

[0121] Robotic system with data capture system Now refer to Figure 5 , which illustrates a schematic diagram of an exemplary robotic medical system with an exemplary data capture system according to an embodiment. In this regard, although Figure 4 The system 100 is illustrated as being provided as a standalone system that can be coupled to a robotic EMD, but Figure 5 Illustrated is a robotic medical system 200 in which a data capture system is implemented.

[0122] therefore, Figure 5 The robotic medical system 200 is provided with a data capture system 120 and an EMD interface 110. Similarly, the data capture system 120 includes a sensor system 122 and Figure 4 The processing unit 124 of the data capture system 120. In addition, the robotic medical system 200 is equipped with one or more EMDs, which are controlled by the robot drive 24. The robot drive 24 responds to commands from the input module 220.

[0123] In turn, the EMD interface 110 may respond to operator input received through 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 may be converted into mechanical or digital input to the EMD interface 110.

[0124] Figure 5 The exemplary robotic medical system 200 may be similar to the one described above with reference to Figure 1-3 The system 10 is described and may include a bedside unit and a control station. The input module 220 and a portion of the data capture system 120 may be provided in the control station, while the one or more EMDs are provided on the bedside unit.

[0125] In one example, the robotic medical system 200 is provided with a single EMD. In other examples, the number of EMDs can be selected for a specific purpose or surgery. Multiple EMDs can be arranged in series, in parallel, or in any other desired arrangement. In one example, utilizing multiple EMDs arranged in series, user input can be applied to the first EMD in the series, and the command is relayed to the additional EMD located downstream by the first EMD. In another example, utilizing multiple EMDs arranged in parallel, the user input from the operator is directly provided 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 the input module 220 allow the operator to operate multiple EMDs simultaneously. Similarly, the sensor system 122 can simultaneously detect and capture the motion and load parameters associated with the operator input applied to multiple EMDs by the robotic system.

[0126] Figure 5 The robotic medical system 200 is provided with a data capture system 120 and an EMD interface 110 to perform the above reference Figure 4 The described archive generation and adaptive guidance capabilities. Of course, the generation of archives and the generation of adaptive guidance parameters can be performed in conjunction with training, simulation, or live surgery. In addition, the generation of archives and the generation of adaptive guidance parameters can be performed as a batch function after capturing data from the surgery. In some examples, the capture of data, the generation of archives, and the generation of adaptive guidance parameters can be performed separately on the same robotic medical system 200 or on different systems 200. In addition, the archives and adaptive guidance parameters generated based on the 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 regard, once the archives 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 surgery.

[0127] 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 profiles and operating rules and restrictions. In other examples, the data capture system can be coupled to the training system 230 or simulator 240 to facilitate training of various operators.

[0128] Now refer to Figure 8 , which illustrates an exemplary data input arrangement and data utilization of a robotic medical system with EMD according to an embodiment. Figure 4 The exemplary data capture system 100 or Figure 5 The data flow of the robotic medical system 200. Figure 8 As shown in FIG, data from an experienced physician 510 can be obtained during live surgery via a measurement system 512 (e.g., Figure 5 The data may be captured by a sensor system 122 (e.g., a sensor system 122). Alternatively, the data may be collected during a training phase or during simulation on a simulator / trainer 522. The captured data is collected, recorded, and processed 514. The captured data may be used to generate a physician profile 516. One or more physician profiles 516 may be used to generate a public profile. For example, as described above, a public profile may be generated to be associated with a particular experience level.

[0129] The newly captured profiles may be used to update the operating rules and limits 518. In this regard, the robotic medical system may use these profiles to teach or guide other operators or to limit various parameters of the robotic medical system.

[0130] like Figure 8 As shown in , a feedback loop can be provided where the use of a robotic system can be used to collect, record or process additional data. The additional data can be used to continuously update the physician's profile.

[0131] In one example, a robotic medical system can be used to obtain limits on loads and motion parameters for an EMD that is to be manipulated by a robotic system. The EMD may be damaged during manipulation by an operator under a particular load, for example, due to buckling, kinking, or breaking. The appropriate ranges of load and motion parameters, such as force, torque, velocity, acceleration, displacement, and combinations of these parameters, depend on the mechanical properties of the EMD and the boundary conditions of the EMD, for example, how the EMD is supported. For an EMD manipulated by a robotic system, in addition to the mechanical properties of the EMD, the appropriate ranges of load and motion parameters to avoid damage to the EMD also depend on the design and characteristics of the robotic drive system. In an exemplary embodiment, Figure 5 The robotic system 200 uses a data capture system to obtain appropriate ranges of loads and motion parameters on the EMD while being manipulated by the robotic medical system. The appropriate ranges can be found during testing that may be destructive or non-destructive. The data capture system stores the captured data during such testing and uses the data in generating operating rules and restrictions 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. The arrangement may involve serial or parallel manipulation of the EMDs. In addition, the processing unit 130 may take into account other factors, such as the constraints of the medical robotic system, to modify the operating rules and restrictions. For example, the processing unit 130 may reduce the maximum linear and rotational speeds of the EMD when there is a delay in the system; for example, this is due to network delays associated with the remote input module.

[0132] According to an embodiment, the data capture system can simultaneously capture linear and rotational motion parameters and force and torque parameters applied to the EMD, or a combination of two or more thereof. Such a data capture system can be independent, such as Figure 4 as shown in , or can be coupled to a robotic medical system, such as Figure 5 As shown in . In one embodiment, the robotic system uses a data capture system that operates in two states. When the robotic system is used to manipulate the EMD via the input module 220 (for example, during surgery or simulation), the data capture system operates in the first state. In this first state, the data capture system captures and stores the motion and load parameters applied by the robotic system to the EMD. In the second state, the EMD is loaded into the robotic system, but is directly manipulated by the operator. In other words, the operator can apply mechanical input to the EMD while the EMD is engaged in the robotic system equipped with the data capture system. In this second state, the robotic 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 by the robotic system to the EMD 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 robotic system generates a profile as well as operating rules and constraints based on the data captured in state 1, state 2, or a combination of the data captured in both states. Such a robotic system allows for customization of load and motion profiles and operating rules / limits based on operator mechanical inputs on the EMD without the need for an additional standalone data capture system.

[0133] As an example of a robotic system with two states as described above, in state 2, the EMD can be engaged in the device module 32 via a chuck. The chuck holds the EMD so that it 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 an operator. Furthermore, the chuck is allowed to rotate in response to a torque applied by the EMD. While linear and rotational movement of the EMD is permitted, the actuator generates an adjustable resistive load to counteract the EMD's movement. The data capture system allows independent resistance and torque to be applied to the EMD. For example, the current of the actuator can be adjusted to adjust the resistive load applied to the EMD by the device module 32. Load parameters can be determined by measuring the current of the actuator, as the load on the actuator is proportional to its current. As another example, a brake can be used on each actuator to generate an adjustable load on the EMD. As another example, the device module 32 does not move and only captures data on the load applied to the EMD by the operator. In another example, sensors can be used to measure the load parameters. A sensor for measuring torque is attached between the actuator for the rotational degree of freedom and the collet that holds the EMD. A sensor for measuring force can be placed between the collet and the device module 32 or between the device module 32 and the base of the sliding member for the linear degree of freedom of the EMD. As another example, the EMD has an embedded load sensor to measure load parameters.

[0134] Exemplary Hardware Now refer to Figure 9-11 , which illustrates various examples of hardware for use with the exemplary robotic medical system or data capture system described herein. Figure 9 , which illustrates an exemplary actuator / sensor arrangement for use with various EMDs, according to an embodiment. Figure 9 The exemplary arrangement 600 shown in FIG can be used to measure force and linear velocity using a single module and simultaneously. Additionally, the exemplary arrangement 600 can be used to measure torque and rotational speed simultaneously.

[0135] Exemplary arrangement 600 is illustrated with an EMD 610 passing therethrough. EMD 610 is clamped with an adjustable friction clamp 620. Clamp 620 may include spring-loaded pads and / or tires that push against EMD 610, allowing for continuous motion of EMD 610. Frictional resistance may be adjusted using, for example, a thumb screw or a motorized system with servo control. Optical sensor 630 is also used to measure motion parameters of the EMD.

[0136] The exemplary arrangement 600 also includes a torquer 640 for clamping the EMD. The operator uses the back side of the torquer ( Figure 9The EMD is manipulated by the torquer (the rightmost side of the torquer). The torquer has one or more sensors 650 to measure the load (force and torque) applied to the EMD by the torquer. Data is captured simultaneously from the optical sensor 630 and the sensor 650.

[0137] Now refer to Figure 10 , which illustrates an exemplary linear sensor system module for use with various EMDs according to embodiments. Exemplary linear module 700 is illustrated with EMD 710 passing therethrough. Exemplary linear module 700 includes friction clamp 720. As described above, friction clamp 720 allows for continuous movement of EMD 710 through linear module 700. Friction clamp 720 includes spring 722 to provide a clamping force on EMD 710. This clamping force can be adjusted using thumb screw 724.

[0138] The 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 a torque spring. When the EMD moves linearly (advancing or retracting), 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 diameter of the tires, the processing unit 124 of the data capture system 120 determines the linear velocity of the EMD. In addition, a force sensor 750 is provided to measure the linear force applied to the EMD 710.

[0139] Now refer to Figure 11 , which illustrates an exemplary rotation sensor system module for use with various EMDs according to an embodiment. An exemplary rotation module 800 is illustrated with an EMD 810 passing therethrough. The exemplary rotation module 800 includes a friction clamp 820 having a clamping plate that allows continuous rotational motion of the EMD 810 through the rotation module 800. The friction clamp 820 applies an adjustable torque to the EMD. The resistance 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.

[0140] The exemplary rotation module 800 includes an encoder 840, such as an optical encoder, to measure rotational displacement, rotational velocity, and / or rotational acceleration. In addition, a torque sensor 830 is provided to measure the torque applied to the EMD 810. The torque and motion parameters are captured simultaneously from the encoder 840 and the torque sensor 830, which can be used to obtain the rotational power applied to the EMD.

[0141] Computer executable instructions for the steps of exemplary methods 300 and 400 may be stored on a form of computer readable media. Computer readable media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer readable media includes, but is not limited to, random access memory (RAM), read-only memory (ROM), electrically erasable programmable ROM (EEPROM), flash memory or other memory technology, compact disk ROM (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or may be used to store the desired instructions and which may be accessed by system 10 ( Figure 1 any other medium accessible through the Internet or other computer network.

[0142] This written description uses examples to disclose the invention, including the best mode, and also to enable 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 occur to those skilled in the art. Such other examples are intended to be 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 with insubstantial differences from the literal language of the claims. The order and sequence of any process or method steps may be changed or re-sequenced according to alternative embodiments.

[0143] Numerous other changes and modifications may be made to the present invention without departing from the spirit of the invention. The scope of these and other variations will become apparent from the appended claims.

[0144] Item 1: A data capture system for generating a profile using captured parameters from a reference operator, comprising: a user interface that receives input from the reference operator for operation of one or more elongated medical devices (EMDs); a sensor system having sensors to capture parameters associated with the input from the reference operator; and a processing unit that uses the captured parameters to generate at least one profile, the profile being associated with characteristics of the reference operator.

[0145] Item 2: A robotic medical system comprising: a module for independently and collaboratively actuating one or more EMDs; a user interface that receives input from a reference operator to manipulate the EMD; a sensor system having sensors to detect motion and / or load parameters applied to the EMD; a data capture portion that captures parameters detected by the sensors associated with the input from the reference operator, the captured parameters including at least one motion or load parameter, wherein the data capture portion associates the captured parameters with characteristics of the reference operator; and a processing unit that converts the detected parameters into operational control equations for the slender medical device and surgery.

[0146] Item 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 operation commands for the robotic device; and using the captured input parameters to generate a profile, the profile being associated with characteristics of the reference operator.

[0147] Item 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 instructions for: capturing input parameters from a reference operator of a robotic device, the captured input parameters comprising at least one motion or load parameter; converting the captured input parameters into operation commands for the robotic device; and generating a profile using the captured input parameters, the profile being associated with characteristics of the reference operator.

[0148] Item 5: A computer-implemented method comprising: capturing input parameters from a reference operator of a robotic device, the captured input parameters comprising at least one motion or load parameter; converting the captured input parameters into operation commands for the robotic device; and using the captured input parameters to generate a profile, the profile being associated with characteristics of the reference operator.

[0149] Item 6: A data capture system comprising: a user interface that receives input from a reference operator for operation of a slender medical device, the user interface including sensors to detect parameters associated with the input from the reference operator; a recording portion that captures parameters associated with the input from the reference operator detected by the sensors, the captured parameters including at least one motion or load parameter; and a processing unit that generates parameters for adaptive guidance of operation of the slender medical device based on the captured input parameters.

[0150] Item 7: A robotic medical system comprising: a user interface that receives input from a reference operator; a sensor system having sensors to detect parameters associated with the input from the reference operator; a data capture portion that captures parameters associated with the input from the reference operator detected by the sensors; a processing unit that converts the input from the operator into operational adaptive guidance for an elongated medical device (EMD) and surgery; and at least one module that independently and collaboratively actuates one or more EMDs.

[0151] Item 8: A method comprising: capturing input parameters from a reference operator of a slender medical device, the captured input parameters including at least one motion or load parameter; converting the captured input parameters into operation commands for the slender medical device; and generating guidance parameters for the slender medical device based on the captured input parameters.

[0152] Item 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 instructions for: capturing input parameters from a reference operator of a robotic device, the captured input parameters comprising at least one motion or load parameter; converting the captured input parameters into operation commands for the robotic device; and generating guidance parameters for an elongated medical device based on the captured input parameters.

[0153] Item 10: A computer-implemented method comprising: capturing input parameters from a reference operator of a robotic device, the captured input parameters comprising at least one motion or load parameter; converting the captured input parameters into operation commands for the robotic device; and generating guidance parameters for an elongated medical device based on the captured input parameters.

[0154] Item 11: A data capture system for generating a profile using captured parameters from a reference operator, comprising: a user interface that receives input from a reference operator for operation of one or more elongated medical devices (EMDs); and a sensor system having sensors to capture 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.

[0155] Item 12: A data capture system for generating a profile using captured parameters from a reference operator, comprising: a user interface that receives input from the reference operator for operation of one or more elongated medical devices (EMDs); and a sensor system having sensors to capture parameters associated with the input from the reference operator; wherein the parameters detected by the sensors include a combination of two or more of a motion parameter, a load parameter, position, displacement, frequency, linear velocity, linear force, rotational velocity, or rotational torque.

[0156] Clause 13: The data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method of any of Clauses 1-12, wherein the parameter detected by the sensor comprises at least one of a motion parameter or a load parameter.

[0157] Clause 14: The data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method of any of clauses 1-13, wherein the motion parameter and the load parameter include at least one of displacement, linear velocity, linear force, rotational velocity, rotational torque, acceleration, or frequency.

[0158] Item 15: A data capture system, a robotic medical system, a method, a non-transitory computer-readable storage medium, or a computer-implemented method as described in any of Items 1-14, wherein the parameter detected by the sensor includes 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 and linear force; or (d) a combination of angular displacement and / or angular velocity and / or angular acceleration and torque.

[0159] Clause 16: The data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method of any of Clauses 1-15, wherein the parameter detected by the sensor comprises a manipulation frequency of the EMD.

[0160] Item 17: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any of Items 1-16, wherein the parameter detected by the sensor includes a combination of two or more of a motion parameter, a load parameter, position, displacement, frequency, linear velocity, linear force, rotational velocity, or rotational torque.

[0161] Clause 18: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any 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.

[0162] Item 19: A data capture system, a robotic medical system, a method, a non-transitory computer-readable storage medium, or a computer-implemented method as described in any of Items 1-18, wherein the sensor system includes contact and / or non-contact sensors to detect movement and / or load of the EMD or a stack of EMDs.

[0163] Clause 20: The data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method of any of Clauses 1-19, wherein the sensor system may include signal conditioning.

[0164] Clause 21: The data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method of any of clauses 1-20, wherein the user interface comprises more than one EMD and the sensor system detects input parameters for concurrent operation of more than one EMD.

[0165] Clause 22: The data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method of any of Clauses 1-21, wherein the parameters are captured based on a heuristic model.

[0166] Clause 23: The data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method of any of Clauses 1-22, wherein the characteristics of the reference operator include at least one of physician metadata.

[0167] Clause 24: The data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method of any of Clauses 1-23, wherein at least a portion of the capture parameters are associated with case metadata.

[0168] Clause 25: The data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method of any of Clauses 1-24, wherein at least a portion of the capture parameters is a combination of physician metadata and case metadata.

[0169] Clause 26: The data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method of any of Clauses 1-25, wherein recording and retrieval of data can be local or non-local to the system.

[0170] Clause 27: The data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method of any of clauses 1-26, wherein the processing unit utilizes an algorithmic analysis of inputs from one or more operators in forming the at least one profile.

[0171] Clause 28: The data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method of any of Clauses 1-27, wherein the processing unit generates a power profile associated with the at least one profile comprising motion and load parameters.

[0172] Clause 29: The data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method of any of Clauses 1-28, wherein the processing unit calculates and determines an envelope of a range of motion, load, and power parameters.

[0173] Item 30: A data capture system, a robotic medical system, a method, a non-transitory computer-readable storage medium, or a computer-implemented method as described in any of Items 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 archive.

[0174] Clause 31: The data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method of any of Clauses 1-30, wherein the processing unit generates a motion profile and / or load profile associated with one or more EMDs.

[0175] Item 32: A data capture system, a robotic medical system, a method, a non-transitory computer-readable storage medium, or a computer-implemented method as described in Item 31, wherein the motion profile is constructed solely based on the motion parameters of the at least one profile for an EMD, including simultaneous rotational and linear motion of the EMD.

[0176] Item 33: A data capture system, a robotic medical system, a method, a non-transitory computer-readable storage medium, or a computer-implemented method as described in Item 31, wherein the motion profile is constructed based on the motion parameters of the at least one profile for more than one EMD, including rotational and / or linear motion of a first EMD and rotational and / or linear motion of a second EMD occurring simultaneously.

[0177] Clause 34: The data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method of clause 31, wherein the motion profile is constructed based on load parameters of the at least one profile for more than one EMD.

[0178] Item 35: The data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method of Item 31, wherein the motion profile is constructed based on both motion and load parameters of the at least one profile for more than one EMD.

[0179] Clause 36: The data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method of any of Clauses 1-35, wherein the processing unit generates the master profile by combining the physician metadata and the case metadata.

[0180] Clause 37: The data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method of any of clauses 1-36, wherein the processing unit combines the capture parameters from the reference operator with additional capture parameters from additional operators to generate an aggregated profile.

[0181] Clause 38: The data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method of any of clauses 1-37, wherein the at least one profile generated by the processing unit is updated with additional captured data from additional additional operators.

[0182] Clause 39: The data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method of any of clauses 1-38, wherein the processing unit updates the profile when new input data is available following ongoing consecutive surgeries.

[0183] Item 40: A data capture system, a robotic medical system, a method, a non-transitory computer-readable storage medium, or a computer-implemented method as described in any of items 1-39, wherein the processing unit converts input from the reference operator in combination with other metadata into operational control equations, operational constraints, and commands.

[0184] Item 41: A data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method as described in any of Items 1-40, wherein the processing unit is capable of generating or updating the at least one profile and converting the data into operating rules offline or in real time.

[0185] Clause 42: The data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method of any of Clauses 1-41, wherein the processing unit provides feedback to the second operator based on the generated profile.

[0186] Clause 43: The data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method of Clause 42, wherein the feedback is provided during a training simulation.

[0187] Clause 44: The data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method of clause 42, wherein the feedback is provided during a live procedure performed by the second operator.

[0188] Clause 45: The data capture system, robotic medical system, method, non-transitory computer-readable storage medium, or computer-implemented method of Clause 42, wherein the second operator is capable of selectively accepting or rejecting the feedback.

[0189] Clause 46: The data capture system, the robotic medical system, the method, the non-transitory computer-readable storage medium, or the computer-implemented method of any of Clauses 1-45, wherein the processing unit generates adaptive guidance parameters.

[0190] Item 47: A data capture system, a robotic medical system, a method, a non-transitory computer-readable storage medium, or a computer-implemented method as described in Item 46, wherein the adaptive guidance parameters include at least one of operational control equations or constraints applied to the EMD or surgery, surgical recommendations, motion profiles, or general rule-based motions and loads.

Claims

1. A robotic medical system comprising: a data capture portion that captures a plurality of parameters sensed by the sensor system, the plurality of parameters being associated with a plurality of inputs from a reference operator; A processing unit that: converting the plurality of inputs into adaptive guidance for the operation of an elongated medical device or a procedure using the elongated medical device, and providing adaptive guidance of the operation to an operator during a simulated or live operation by the operator; and At least one module that independently and cooperatively actuates the elongated medical device.

2. The robotic medical system according to claim 1, further comprising: A user interface receives the plurality of inputs from the reference operator.

3. The robotic medical system according to claim 1, wherein: The sensor system includes a plurality of sensors to detect the plurality of parameters.

4. The robotic medical system according to claim 3, wherein: The plurality of sensors includes at least one of a contact or non-contact sensor to detect at least one of motion or load of the elongated medical device or a stack of elongated medical devices.

5. The robotic medical system according to claim 1, wherein: The plurality of parameters includes at least one motion or load parameter.

6. The robotic medical system according to claim 5, wherein: The at least one motion or load parameter includes at least one of displacement, linear velocity, linear force, rotational velocity, rotational torque, acceleration, or frequency.

7. The robotic medical system according to claim 5, wherein: The at least one motion or load parameter includes at least one of: (a) a combination of linear velocity and linear force; (b) a combination of rotational velocity and rotational torque; (c) a combination of at least one of displacement, velocity, or acceleration and linear force; or (d) a combination of at least one of angular displacement, angular velocity, or angular acceleration and torque.

8. The robotic medical system according to claim 5, wherein: The at least one motion or load parameter comprises a manipulation frequency of the elongate medical device.

9. The robotic medical system according to claim 5, wherein: The at least one motion or load parameter includes a combination of two or more of a motion parameter, a load parameter, position, displacement, frequency, linear velocity, linear force, rotational velocity, or rotational torque.

10. The robotic medical system according to claim 1, wherein: The processing unit is configured to provide further adaptive guidance including surgical recommendations, motion profiles, or general rule-based motions and loads applied to the elongated medical device or a procedure using the elongated medical device.

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