590 results about "Robotic surgery" patented technology

A federated distributed computational system enables secure biological data analysis and genomic medicine with enhanced oncological therapy capabilities. The system implements patient-specific tumor-on-a-chip analysis through microfluidic control systems and cellular heterogeneity preservation, while integrating fluorescence-enhanced diagnostics using CRISPR-LNP targeting and robotic surgical navigation. The architecture coordinates spatiotemporal analysis of gene therapy delivery through molecular imaging and immune response tracking, and implements bridge RNA integration with multi-target synchronization. Treatment selection is optimized through multi-criteria scoring and patient-specific simulation modeling. Each federated node contains a local processing unit for biological data analysis, privacy preservation protocols, and a hierarchical knowledge graph structure. The system implements cross-species genetic analysis, environmental response modeling, and multi-scale tensor-based data integration, enabling research institutions to collaborate on complex, large-scale biological analyses while maintaining strict data privacy controls.

A robotic surgical system includes a surgeon consol coupled to a patient consol, and the patient consol coupled to surgical instruments. A surgeon computer is coupled to or at the surgeon consol that is coupled to to one or more surgical instruments. A robotic surgery control system includes an artificial intelligence (AI) system with one or more deep learning algorithms. A feedback loop monitors and collects data from the one or more sensors. One or more cameras provide feedback to the robotic surgical system, and are configured to provide images of an anatomical object in at least a two dimensional (2D) arrangements of pixels / Deep learning algorithms of the AI system distinguish different anatomical objects from the images.

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. 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.

This application is directed to systems, methods, and devices for image based analysis of plaque. In some embodiments, the approaches herein can be used for developing treatment plans, which can include local treatment, systemic treatment, or both. In some embodiments, the approaches herein can be used for stent selection. In some embodiments, the approaches herein can be used for surgical planning, which can include robotic surgical planning. In some embodiments, the approaches herein can be used for image normalization. In some embodiments, the approaches herein can be used for identifying plaque calcification thresholds. In some embodiments, the approaches herein can be used for identifying thin cap fibroatheroma. In some embodiments, the approaches herein can be used for coronary artery tree reconstruction. Some embodiments are directed to coronary artery disease risk stratification.

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.

This application is directed to systems, methods, and devices for image based analysis of plaque. In some embodiments, the approaches herein can be used for developing treatment plans, which can include local treatment, systemic treatment, or both. In some embodiments, the approaches herein can be used for stent selection. In some embodiments, the approaches herein can be used for surgical planning, which can include robotic surgical planning. In some embodiments, the approaches herein can be used for image normalization. In some embodiments, the approaches herein can be used for identifying plaque calcification thresholds. In some embodiments, the approaches herein can be used for identifying thin cap fibroatheroma. In some embodiments, the approaches herein can be used for coronary artery tree reconstruction. Some embodiments are directed to coronary artery disease risk stratification.

Systems and subsystems for closing an end effector of a stapler are disclosed. More specifically, the present disclosure relates to systems, devices, and subsystems for attachments for robotic surgeries. The surgical instrument is a robotic attachment. The surgical instrument includes a closure subsystem that moves independently of other subsystems that are operable independently of each other.

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 robotic surgical system network includes a plurality of robotic surgical systems. Each system includes robotic arms, sensors, a surgeon console, and a control system with an integrated AI module. A network interface is associated with robotic surgical system and provides secure data communication. A central or distributed data repository securely stores surgical data aggregated from the robotic surgical systems. The surgical data includes at least one of procedural data, sensor readings, imaging data, AI decision logs, surgical outcomes, or user interaction data. A training module utilizes aggregated surgical data to train or update AI models for the robotic surgical systems using unsupervised learning, transfer learning, or federated learning techniques. A cybersecurity module implements security measures for data transmission and system access, the measures comprising at least one of encryption, multi-factor authentication, or real-time threat detection.

A dynamic reference base (DRB) and associated method are provided for rigidly affixing an array frame to bone for use in navigated or robotic surgery. The DRB includes a bridge element that includes a connecting rod having a distal end and a proximal end; a clamp coupled to the distal end of the connecting rod; a first and a second pin guide extending distally from the clamp; a locking nut disposed on the clamp; and a clutch coupled to the proximal end of the connecting rod, the clutch being adapted to couple to the array frame. The DRB also includes the array frame, which is couplable to the clutch, and is adapted to include a plurality of tracking markers disposed thereon.

The invention involves a system and method for increasing positional accuracy of surgical systems that utilize magnetic or electromagnetic sensors to provide positional awareness to a surgeon or robot performing the surgery. The system takes advantage of electromagnetic tracking through sensors. These sensors are very accurate and repeatable, while being compact enough to not inhibit surgical procedures. The accuracy and repeatability of the sensors is <1 mm within a predetermined 6 inch×6 inch performance motion box. The system is constructed and arranged to map the distortion patterns of the sensor and, in real time, correct the distortion pattern to provide accurate location of anatomical structures for performance of a surgery.

Teleoperative, partially automated, and fully automated robotic surgery systems and methods are described herein. These systems and methods relate to at least improvement of robotic movements, three dimensional tracking and pose correction for robots interacting with deformable objections, controlling and optimizing the redundant axis of a seven degree of freedom robotic arm, virtual robotic surgery and simulation, and task coordination and optimization for multi-robot surgery.

An ultrasonic surgical device comprising of a proximal end and a distal end to be used in a robotic surgical system. The distal end comprises of a first jaw with an ultrasound transducer array and a second jaw with either a reflecting surface or an ultrasound transducer array. The distal end is configured to grasp a blood vessel or a living tissue. The proximal end is configured to apply a drive signal to the ultrasound transducer array. A plurality of rotary joints is connected at the distal end to facilitate its articulation. The ultrasound transducer array, generates acoustic vibrations in the grasped blood vessel, or living tissue, based on the applied drive signal by a control system of the robotic surgical system. The ultrasound transducer array, is configured to sense parameters of a target site on a grasped blood vessel or living tissue, based on the reflected acoustic vibrations.

Systems and methods for eye tracking and content tagging in minimally invasive surgical videos are described herein. Minimally invasive surgical videos may be captured while performing robotic surgeries. Robotic surgical systems described herein include robotic arms with interchangeable surgical tools. An endoscope at the end of one of the robotic arms captures video of the surgical procedure. The video is displayed on a display of the surgical system and an eye tracking device captures data corresponding to a gaze direction of the user on the display. Content tags are automatically generated in the image data based on areas of focus of the user. Information within the content tag may be generated based on surgical procedure steps derived from the image data, a log of current surgical procedures, and image data of previous surgical procedures.

Robotic surgical systems configured to control the movement and actuation of a single robotic arm, and the movement and actuation of first and second tools carried in a tool holder at a distal end of the robotic arm.

Systems and methods for surgical robotic collision detection in accordance with aspects of the present disclosure are disclosed. In various embodiments, a system for surgical robotic collision detection includes a robotic cart having a robotic arm, an imaging device supported by the robotic cart or the robotic arm, the imaging device captures images within a field of vision of the imaging device, and a controller in operable communication with the robotic arm and the imaging device. The controller includes a processor and a memory storing instructions which, when executed by the processor, causes the controller to: receive the images from the imaging device, generate a grid including a first plurality of spatial points from the images, and detect a potential collision within the field of vision based on the generated grid.

Robot calibration is crucial in multi-robot cooperative systems where the inaccuracy of robots can add up and cause large errors in the final trajectory of handled parts or process tools. In this work, a two-step calibration approach is proposed based on artificial neural networks (ANNs) and definition of compensated pose for a master-slave cooperative robot system. Measuring the pose of master and slave robots at different locations in their shared workspace is required to create pairs of joint angles and output pose errors as training data. The generated data is used to train two ANN models for compensating the master-slave relative error and the master robot errors. The master-slave relative error is corrected by introducing a compensated pose for the slave robot with respect to the master robot. A neural network is then trained to predict the error parameters of the compensated pose for the joint angles of both robots as the input. The master robot is then corrected individually using another ANN model to address the absolute accuracy of the cooperative system.Measurements and simulations have been performed on a dual-robot cooperative system before and after geometric calibration. The process of cross validation is carried out to find the best network architecture for the optimal performance in correcting the robots'errors. It has been shown that even after pre-existing model-based calibration of each robot, both the absolute accuracy of the master robot and the relative tracking accuracy can be further improved by the proposed implementation of ANN calibration.

Systems and methods for surgical robotic collision detection in accordance with aspects of the present disclosure are disclosed. In various embodiments, a system for surgical robotic collision detection includes a robotic cart having a robotic arm, an imaging device supported by the robotic cart or the robotic arm, the imaging device captures images within a field of vision of the imaging device, and a controller in operable communication with the robotic arm and the imaging device. The controller includes a processor and a memory storing instructions which, when executed by the processor, causes the controller to: receive the images from the imaging device, generate a grid including a first plurality of spatial points from the images, and detect a potential collision within the field of vision based on the generated grid.

Certain aspects relate to systems and techniques for a drape for covering an adjustable arm support of a robotic surgical system. In one aspect, the drape includes a drape portion configured to extend over the adjustable arm support. The drape may include at least two tubular sleeves configured to surround the at least two robotic arms. The at least two robotic arms can be slidable relative to each other along the adjustable arm support. The drape portion can cover an area between the at least two tubular sleeves.

The invention provides an artificial cochlea electrode implantation system and method, and relates to the technical field of artificial cochlea electrode implantation, the artificial cochlea electrode implantation system comprises a data layer and an execution layer, the data layer comprises an image processing module and a postoperative evaluation module, and the image processing module comprises an image acquisition unit, a data processing unit, a model construction unit and a data integration unit. The postoperative evaluation module comprises a data analysis unit and a result storage unit, the execution layer comprises a high-precision grinding module and an intelligent control module, the high-precision grinding module comprises an electric drill unit, a navigation unit and a robot surgery unit, and the intelligent control module comprises a computer auxiliary unit, a sensor unit and an alarm unit; under the guidance of preoperative image data and a navigation system, an electric drill is used for grinding an electrode implantation passage, meanwhile, the operation efficiency can be improved, the electrode implantation does not need to pass through a retroauricular incision, and only an intraauricular incision needs to be made to implant the electrode into the cochlea, so that the success rate of an artificial cochlea operation and the life quality of a patient are improved.

Described here are systems, devices, and methods useful for minimally invasive surgical procedures performed by a single operator. A robotic surgery system may include a robotic arm having a coupling mechanism for releasably coupling to an end effector connector. Methods for removably coupling the robotic surgery system may include coupling the end effector connector to the coupling mechanism, actuating the coupling mechanism to release the end effector connector, and receiving the end effector connector. The coupling, actuating, and receiving may be performed with a single hand of an operator. Additionally, devices for performing minimally invasive surgery may include a robotic arm input device having independently controllable foot-actuated switches. Methods for using the input device may include receiving a robotic arm control signal based on single-footed operation of the input device and controlling a movement of the robotic arm accordingly.

A method of controlling a surgical system includes obtaining a surgical plan containing a plurality of planned cuts, receiving a first cutting tool from a plurality of cutting tools at a surgical device, collecting a first checkpoint by tracking a probe as the probe contacts a first predefined point on the first cutting tool, collecting a second checkpoint by tracking the probe as the probe contacts a second predefined point at a first bone of a patient, automatically selecting a first planned cut from the plurality of planned cuts based on the first checkpoint and the second checkpoint, and, in response to automatically selecting the first planned cut, guiding execution of the first planned cut using the first cutting tool.

Surgical systems and methods for manipulation of an anatomy that includes cortical and cancellous bone. A surgical manipulator has a robotic arm to move an instrument with an energy applicator. A sensor senses forces / torques applied to the energy applicator. Controller(s) obtain a tool path for the energy applicator to traverse. A segment of the tool path transitions into, or between, cortical bone and cancellous bone. The controller(s) control the manipulator to advance the energy applicator along the tool path according to a first feed rate to manipulate the cortical or cancellous bone and detect, with the sensor, a change in the forces / torques being indicative of the transition. In response to detection of this change, the controller(s) control the manipulator to advance the energy applicator along the tool path according to a second feed rate, greater / less than the first feed rate.

A gearbox assembly and surgical instrument including the same. The gearbox assembly includes a drive gear including a round gear and a lead screw such that a rotational input to the round gear rotates the lead screw. A first hub is threadingly engaged about the lead screw such that rotation of the lead screw translates the first hub. A second hub is spaced-apart from the first hub and engaged with a drive rod. A compression spring is disposed between the hubs. When a force acting against the drive rod is below a threshold, the rotational input translates the first hub, compression spring, second hub, and drive rod. When the force is equal to or above the threshold, the rotational input translates the first hub and compresses the compression spring against the second hub to maintain the second hub and drive rod in position.

A method for improved robotic cutting, the method comprising: determining at least one of cutting force data and bone motion data during robotic cutting; determining when at least one of the cutting force data and bone motion data exceeds a predetermined parameter; and when it is determined that at least one of the cutting force data and the bone motion data exceeds the predetermined parameter, providing the user with an indication of the same and pausing the robotic cutting so as to enable the user to mitigate the cause of at least one of the cutting force data and the bone motion data exceeding the predetermined parameter.

An insertable robot for minimally invasive surgery includes a tube array having a guide tube housed within a straightening tube. The guide tube includes a curved working end. The guide tube may be axially translated and rotated relative to the straightening tube such that the curved working end is constrained inside the straightening tube, causing the curved working end to achieve a smaller dimension. The tube array is inserted into a working channel on an endoscope, resectoscope or trocar. Once the tube array is inserted, the curved working end of the guide tube is translated forward beyond the distal end of the working channel, allowing the curved working end to return to its pre-formed shape. A surgical tool is inserted through the guide tube for an operation. The straightening tube allows the guide tube curved working end to be temporarily straightened during insertion and removal of the tube array.

Graphical user guidance for a robotic surgical system is provided. In one embodiment, a graphical user interface for a robotic surgical system comprises a first region and a second region. The first region is used to display an endoscopic view of a surgical site inside a patient taken by an endoscopic camera of the robotic surgical system, and the second region is used to display user feedback information. The graphical user interface overlays a guidance message on top of the endoscopic view of the surgical site in the first region to provide user instructions for interacting with a user input device to engage a robotic arm of the robotic surgical system. Other embodiments are provided.

A robotic surgical system includes a surgical instrument, a robotic arm, and a coupler assembly. The surgical instrument defines a longitudinal axis therethrough and supports an end effector on a free distal end portion of the surgical instrument. The robotic arm includes segments that are movably coupled together by joints. A first joint has at least two degrees of freedom for positioning the surgical instrument relative to a patient. The coupler assembly removably couples the surgical instrument to the robotic arm. The coupler assembly is positioned to enable the surgical instrument to rotate about the longitudinal axis and relative to the robotic arm.