8088results about "Surgical manipulators" patented technology

A surgical visualization system for use with a robotic surgical system that includes a surgical tool movable with respect to a tissue of a patient in response to an instrument motion control signal is disclosed. The surgical visualization system includes a camera and a control circuit coupled to the camera. The control circuit is configured to determine a distance between the surgical tool and the tissue and adjust a magnification of the camera based on the distance between the surgical tool and the tissue.

One or more data streams may be used for controlling multi-system interaction. For example, a data stream may be received, and a surgical option associated with a surgical instrument may be selected based on the data stream. A control signal associated with the surgical instrument may be generated based on the selected surgical option. A surgical device may receive an external data stream from a source external to the surgical system. The device may derive, based at least on the external data stream, decision contextual information. The device may select a surgical option associated with a surgical instrument based on the decision context information. The device may generate a visual indication of the decision context information associated with selecting the surgical option. The device may generate a control signal associated with the surgical instrument based on the selected surgical option.

A modular surgical system for use in a surgical procedure is disclosed. The modular surgical system includes a control module including a power supply and surgical modules including a first surgical module and a second surgical module. The first surgical module is arranged in a stack configuration with the control module and the second surgical module. The power supply is configured to output power to the first surgical module and the second surgical module. A power backplane is configured to deliver the power to the first surgical module and the second surgical module through the first surgical module. A control circuit is configured to adaptively adjust power allocations to the first surgical module and the second surgical module.

Systems, methods, and instrumentalities are disclosed for displaying a magnitude and location of a resulting tissue tension from an applied force to an instrument and a resulting tissue reaction. A surgical stapling device for monitoring and adapting to tissue tension during a surgical stapling procedure may measure strain on at least one component of the surgical stapling device resultant from one or more of an opposed force applied by a user and a force resisted by tissue associated with the tissue tension. The device may determine a location of the tissue tension based on historical surgical data, the opposed force, and the resisted force. The device may highlight the location of the tissue tension to aid in real-time surgical decision-making.

The disclosed embodiments relate to systems and methods for a surgical tool or a surgical robotic system. A tool driver is coupled to a distal end of a robotic arm and includes a roll drive disk driven by a rotary motor. One or more processors are configured to detect an attachment of a surgical tool to the tool driver. The surgical tool includes a roll tool disk to be engaged with the roll drive disk of the tool driver, actuate of the roll drive disk through the rotary motor, determine that a measured torque of the rotary motor exceeds a preset torque threshold for a preset period of time since the actuation, and report a successful engagement between the roll drive disk and the roll tool disk.

A system comprises a processor and a memory having computer readable instructions stored thereon, which, when executed by the processor, cause the system to display an image of a surgical environment. The image includes an information icon corresponding to an instrument in the surgical environment. The instructions further cause the system to display an image of a body part of a user. The image of the body part is used to interact with the information icon. The instructions further cause the system to receive a gesture of the body part, via a gesture-based input device registering movement of the body part, to cause the image of the body part to interact with the information icon. The instructions further cause the system to display an information menu in the image of the surgical environment based on the interaction between the image of the body part and the information icon.

The invention discloses a surgical robot resection navigation method based on multi-modal image registration. The method comprises the following steps: acquiring a preoperative multi-modal medical image of a patient and reconstructing a three-dimensional model containing a focus and a dangerous structure; acquiring an intraoperative real-time image; extracting cross-modal invariant features from the pre-operative and intra-operative images by using a first deep learning network, and establishing an initial corresponding relation; predicting an initial non-rigid deformation field by using a second deep learning network, based on the pre-operative / intra-operative image and the initial corresponding relation and in combination with physical model constraints; tracking a surgical tool in real time, and updating a non-rigid deformation field in real time by adopting an incremental calculation strategy; applying the updated deformation field to the preoperative three-dimensional model to generate a deformed model; and mapping the tool position to the deformed model, and generating a navigation instruction. According to the method, soft tissue deformation can be accurately compensated, multi-modal image information is effectively fused, navigation information is dynamically updated in real time, and the precision and safety of robot surgery are remarkably improved.

A robotic surgical system includes a surgeon consol coupled to a patient console and coupled to one or more surgical instruments. The surgeon consol is used by a surgeon to perform a surgical procedure. A surgeon computer is coupled to or at the surgeon console. The surgeon consol is coupled to the one or more surgical instruments. A surgical robot is coupled to a robotic surgery control system and a feedback loop. The robotic surgery control system includes or is coupled to an artificial intelligence (AI) system. The feedback loop receives data from one or more sensors at the robotic surgical system. The data is analyzed by the robotic surgery control system, and in response operation of the robotic surgical system is adjusted as needed. The surgical control system or the AI system uses intraoperative data describing a surgical procedure being performed. The feedback loop receives data from one or more sensors of the robotic surgical system regarding performance of at least a portion of the robotic surgical system. The data is analyzed by the robotic surgical control system. In response to analysis, operation of the robotic surgical system is adjusted as needed. The robotic surgical control system or AI system extracts one or more programmed steps used by the surgeon for positioning at least one of the surgical instruments during the surgical procedure.

A robotic surgical system. a surgeon console operatively coupled to a patient console and one or more surgical instruments. A surgeon computer is coupled to or integrated with the surgeon console, the surgeon computer further operatively connected to the one or more surgical instruments; A surgical robot is coupled to a robotic surgery control system and a feedback loop. The robotic surgery control system includes or is coupled to an artificial intelligence (AI) system. A feedback loop is further configured to receive performance-related data from the one or more sensors, the data analyzed by the robotic surgery control system or the AI system to dynamically adjust the robotic system's operation as needed. A data extraction module retrieves, from the robotic surgery control system or the AI system. one or more programmed steps executed by the surgeon for positioning at least one of the surgical instruments during the surgical procedure.

A surgical device is provided that can implement a bending mechanism by including a bendable element at the distal end. [Solution] A surgical device (1) is provided, which includes a steerable member that is bendable and includes a plurality of bending segments with channels therein, and a plurality of bending actuation wires that are arranged to pass through the steerable member and bend the steerable member, the steerable member including at least one outwardly opening lumen, and the bending actuation wires passing through the lumens.

A method of performing a neurovascular procedure includes the steps of providing an access catheter having an access catheter hub; coupling the access catheter hub to a hub adapter, movably carried by a support table; driving the access catheter in response to movement of the hub adapter along the table until the access catheter is positioned to achieve supra-aortic vessel access; removing the access catheter and access catheter hub from the hub adapter; and coupling a procedure catheter hub having a procedure catheter to the hub adapter.

A medical device includes a manual drive structure having a manual drive input member and a manual drive coupling member. The medical device also includes a first tool drive member including a first motor drive input member and a second tool drive member including a second motor drive input member. The first tool drive member is coupled to and driven by the manual drive input member via the manual drive coupling member and the second tool drive member is coupled to and driven by the manual drive input member via the manual drive coupling member.

The invention relates to the technical field of surgical robot motion control, and discloses a surgical robot motion planning method based on a diffusion model, and the method comprises the steps: obtaining obstacle point cloud data, an initial posture and a target posture in a surgical environment; encoding the obstacle point cloud data into a potential space, and combining the encoded information with the initial attitude and the target attitude into a condition code; a Transform structure of an encoder is adopted to replace a U-Net structure in a traditional diffusion model, and the diffusion model is trained through forward diffusion and reverse denoising processes; in training, using a comprehensive loss function to optimize model performance, combining configuration space loss, geometric task space loss and collision loss, and introducing physical constraints to ensure that the trajectory conforms to kinematic characteristics and avoid collision; and in the operation task, generating a motion track based on the trained diffusion model. According to the invention, the motion planning efficiency and safety of the surgical robot in a complex environment can be improved.

Co-manipulation robotic systems are described herein that may be used for assisting with laparoscopic surgical procedures. The co-manipulation robotic systems allow a surgeon to use commercially-available surgical instruments while providing benefits associated with surgical robotics. Further, the co-manipulation robotic system may operate in multiple modes to enhance usability and safety, while allowing the surgeon to position the instrument directly with the instrument handle and further maintain the desired position of the instrument or a desired force applied by the instrument using the robot arm. For example, the robot arm may be moved automatically to maintain a constant tension force on an anatomical structure via the instrument in a constant tension mode.

A robotic surgical system includes a robotic manipulator configured to perform surgical procedures under direct surgeon control. A surgical camera system captures real-time intraoperative video. An external imaging interface receives multimodal imaging data, including preoperative and intraoperative data from at least one of magnetic resonance imaging (MRI), computed tomography (CT), ultrasound, and fluoroscopy. An artificial intelligence (AI module has a trained neural network and a deep learning model trained on multi-institutional annotated surgical datasets, The AI module is configured to execute one or more of: fuse acquired video and imaging data into temporally and spatially coherent anatomical visualizations; generate continuously updating overlays aligned with the surgical field, with segmented anatomical features; projected tissue boundaries, proximity indicators for instruments, and predictive deformation trends; provide dynamic predictive trend visualization indicating zones of future anatomical complexity or risk; register and align preoperative imaging data with intraoperative imaging data in real time; adapt overlay presentation in response to tissue deformation without actuating the robotic manipulate or; and passively augment visual feedback without initiating any autonomous actuation of surgical instruments.

A robotic surgical system includes one or more robotic actuators configured to interact with biological tissue during a surgical procedure. A plurality of sensors include at least one of fiber Bragg grating sensors, piezoelectric strain sensors, or magnetostrictive sensors to capture real-time mechanical, elasticity, or deformation data from biological tissues. deep learning engine trained on a dataset comprising tissue mechanical responses across multiple tissue types, pathological states, and patient demographics. Pre-contact predictive adjustment profiles are generated for anticipated tissue interactions using preoperative imaging data registered to intraoperative coordinates. Intraoperative deviations are detected from predicted mechanical behavior and autonomously recalibrate actuator forces. Upcoming surgical maneuvers are anticipated based on prior task sequences and adjust actuator stiffness or damping properties in preparation for anticipated contact. An emergency override of actuator forces is provided via an anomaly detection module when real-time sensor data deviates beyond a threshold from the predicted safe mechanical response range. A feedback loop iteratively refines the deep learning engine during the procedure using supervised learning updates, anomaly detection, and reinforcement learning strategies. The reinforcement learning model is optionally shared across procedures to optimize distributed actuator force patterns for minimizing localized and cumulative tissue stress.

The present invention relates to a flexible continuum joint, a flexible robotic arm, and a minimally invasive surgical robot for TEM. The flexible continuum joint comprises a double-helix structure formed by two helical springs, wherein a central channel is provided inside the double-helix structure, a hollow tube arranged coaxially with the double-helix structure is provided in the central channel, and a plurality of notches are formed on the hollow tube. The flexible robotic arm is composed of a linkage joint formed by an active section and a passive section, and an end joint, wherein the active section and the end joint are both driven by a drive wire, and the passive section is driven by a nickel-titanium alloy rod. The minimally invasive surgical robot comprises an endoscopic arm and two robotic arms, and has 19 degrees of freedom overall. In addition, the provision of the linkage joint in the flexible robotic arm and the application of a hybrid drive mode combining a drive wire and a nickel-titanium alloy rod not only reduces the number of drives, but also avoids the problem of motion coupling between joints, thus effectively overcoming the problems of insufficient degrees of freedom and poor motion accuracy in existing minimally invasive surgical robots for TEM.

The invention relates to the technical field of artificial intelligence and data processing, in particular to a surgical robot quality control and fault prediction method based on artificial intelligence, and the method specifically comprises the following steps: collecting the data of a surgical robot through a sensor, carrying out the manual marking of the collected data, and forming a sample data set; performing multi-scale normalization processing on the sample data set; constructing a fault prediction model of the surgical robot by adopting a convolutional neural network, and inputting normalized data into the model for training to obtain a trained fault prediction model; preprocessing the collected new data, inputting the preprocessed data into the trained fault prediction model, and outputting a fault category prediction result corresponding to the input data by the fault prediction model; and constructing a three-dimensional quality control matrix, wherein the three-dimensional quality control matrix triggers a corresponding automatic calibration program based on a category prediction result output by the fault prediction model. According to the method, the fault features of the surgical robot can be accurately captured, and the accuracy of fault prediction and the generalization ability of the model are improved.

A system comprises an EMD and coupled to a robotic drive. The EMD includes an external member defining a lumen and an internal member disposed in the lumen and coupled to a distal portion of the external member, and a linearly and rotationally-actuatable element coupled to the external member. The robotic drive includes a plurality of device modules, each of the plurality of device modules being independently linearly movable by the robotic drive, a first cassette coupled to a first one of the plurality of device modules and to the linearly and rotationally-actuatable element of the external member, and a second cassette coupled to a second one of the plurality of device modules and to the internal member.

Co-manipulation robotic systems are described herein that may be used for assisting with laparoscopic surgical procedures. The co-manipulation robotic systems allow a surgeon to use commercially-available surgical tools while providing benefits associated with surgical robotics. Advantageously, the surgical tools may be seamlessly coupled to the robot arms using a disposable coupler while the reusable portions of the robot arm remain in a sterile drape. Further, the co-manipulation robotic system may operate in multiple modes to enhance usability and safety, while allowing the surgeon to position the instrument directly with the instrument handle and further maintain the desired position of the instrument using the robot arm.

An ultrasonic surgical instrument includes an end effector including an ultrasonic blade, an ultrasonic waveguide, an ultrasonic transducer assembly, and a carrier. The acoustic waveguide includes at least a proximal portion thereof extending along a longitudinal axis. The ultrasonic transducer assembly includes a fixation member and is operatively connected to the acoustic waveguide such that the acoustic waveguide is in acoustic communication with an ultrasonic transducer. The carrier has at least a portion thereof engaged with the fixation member of the ultrasonic transducer assembly thereby inhibiting movement of the ultrasonic transducer assembly relative to the carrier. The carrier movably supports the ultrasonic transducer assembly along the longitudinal axis such that the ultrasonic transducer assembly is configured to move from a proximal position on the longitudinal axis to a distal position on the longitudinal axis for inserting the ultrasonic blade into a patient.

A steerable instrument has a deflectable tip portion (13; 74; 75) at a distal side. A first steering wire (16(1); 429) is attached to the deflectable tip portion (13; 74, 75). The first steering wire (16(1); 429) is part of a tube (3; 102, 103; 121) and is separated from other parts of the tube (3; 102, 103; 121) by a first material removal pattern such that the first steering wire (16(1); 429) extends from a proximal end to a distal end of the steerable instrument. The steerable instrument has a steering unit with a control tube portion (301a(i); 302a(1,3); 431) coaxially arranged with the tube (3). The control tube portion (301a(i); 302a(1,3); 431) controls rotation of the first control tube portion (301a(i); 302a(1,3)) which causes longitudinal movement of the steering wire (16(1); 429) in order to deflect the deflectable tip portion (13; 74; 75)) in a first plane.

Co-manipulation robotic systems are described herein that may be used for assisting with laparoscopic surgical procedures. The co-manipulation robotic systems allow a surgeon to use commercially-available surgical tools while providing benefits associated with surgical robotics. Advantageously, the surgical tools may be seamlessly coupled to the robot arms using a disposable coupler while the reusable portions of the robot arm remain in a sterile drape. Further, the co-manipulation robotic system may operate in multiple modes to enhance usability and safety, while allowing the surgeon to position the instrument directly with the instrument handle and further maintain the desired position of the instrument using the robot arm.

The invention provides a surgical robot control method and device based on body intelligence. The method comprises the steps that a reward function based on inverse reinforcement learning processing is acquired; determining constraint conditions based on differences between past experience scenes and application scenes; based on multi-objective optimization, the operation strategy of the mechanical arm of the surgical robot is trained through reinforcement learning; after training is completed, selecting a moving track with the highest accumulated reward, and controlling a mechanical arm of the surgical robot to execute the moving track; the multi-objective optimization comprises a plurality of objective functions, and the objective functions at least comprise the reward functions and the constraint conditions. According to the method, the difference is converted into the constraint condition, strategy training is carried out in a multi-objective optimization mode, and therefore the problem that adaptation is difficult to carry out due to the difference between operation experience and data of a new surgical robot is solved.

Novel tools and techniques are provided for implementing intelligent assistance (“IA”) ecosystem, and, in some cases, for implementing extended reality (“XR”) for cardiac arrhythmia procedures. In various embodiments, a computing system might receive device data associated with a device(s) configured to perform a cardiac arrhythmia procedure to provide effective heart rhythm, might receive imaging data associated with an imaging device(s) configured to generate images of a portion(s) of a patient. The computing system might analyze the received device data and imaging data (collectively “received data”), might map the received data to a 3D or 4D representation of the portion(s) of the patient based on the analysis, and might generate and present (using a user experience (“UX”) device) one or more XR images or experiences based on the mapping.

An ultrasonic surgical instrument includes an end effector having an ultrasonic blade, an ultrasonic transducer assembly, and a shaft assembly. The shaft assembly includes a tube, and an waveguide. The waveguide is received within the tube and is acoustically connected between the ultrasonic blade and ultrasonic transducer assembly to communicate ultrasonic vibrations from the ultrasonic transducer assembly to the ultrasonic blade. The waveguide includes an acoustic body, a first isolation structure, a second isolation structure and a sheath. The acoustic body extends along a longitudinal axis. The first isolation structure radially extends about the acoustic body. The second isolation structure radially extends about the acoustic body and is longitudinally spaced from the first isolation structure. The sheath is radially positioned between the first isolation structure and the tube and is further radially positioned between the second isolation structure.

Co-manipulation robotic systems are described herein that may be used for assisting with surgical procedures, including laparoscopic surgery. The co-manipulation robotic systems allow a surgeon to use commercially-available surgical tools while providing benefits associated with surgical robotics. Advantageously, the surgical tools may be seamlessly coupled to the robot arms using a disposable coupler while the reusable portions of the robot arm remain in a sterile drape. Further, the co-manipulation robotic system may operate in multiple modes to enhance usability and safety, while allowing the surgeon to position the instrument directly with the instrument handle and further maintain the desired position of the instrument using the robot arm.

The present disclosure provides a staple cartridge for a surgical instrument, such as a tissue sealing instrument. The staple cartridge includes a housing and one or more staple assemblies within the housing. The staple assemblies each include one or more staple pushers and associated staples. The staple pushers and housing include coupling elements configured to cooperate with each other to retain the staple assemblies to the housing prior to use in surgery. The coupling elements, along with other components of the cartridge and instrument, result in a smaller staple cartridge relative to conventional devices, allowing for a more compact and maneuverable surgical instrument.

Co-manipulation robotic systems are described herein that may be used for assisting with surgical procedures, including laparoscopic surgery. The co-manipulation robotic systems allow a surgeon to use commercially-available surgical tools while providing benefits associated with surgical robotics. Advantageously, the surgical tools may be seamlessly coupled to the robot arms using a disposable coupler while the reusable portions of the robot arm remain in a sterile drape. Further, the co-manipulation robotic system may operate in multiple modes to enhance usability and safety, while allowing the surgeon to position the instrument directly with the instrument handle and further maintain the desired position of the instrument using the robot arm.

A surgical instrument designed to operate with a robotic platform is disclosed. The surgical instrument assembly includes a shaft, an end effector, a knife firing subsystem to actuate functions of the end effector, an articulation subsystem that is actuatable to articulate the end effector, an articulation joint about which the end effector articulates, a roll subsystem to roll the shaft, and a housing that couples to the robotic platform.