816 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 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.

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.

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 tool holder interchangeably hold both conventional surgical tools and surgical tools designed specifically for the holder. The tool holder will usually hold but not drive the conventional tools while both holding and driving those tools designed specifically for the tool holder. The tool holder is detachably mounted on a distal end of a surgical robotic arm and has an opening which removably receives individual surgical tools of either type. A drive train in the housing has one input which is driven by the surgical robotic arm and separate outputs for both a tool gripper and a tool driver.

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 methods for autonomous robotic surgery are provided to control a movement of a robotic device so as to perform a surgical procedural step, wherein controlling of the movement is based on information including a spatial position and orientation of at least a part of the robotic device. A trigger information may cause the system to pause or stop the surgical procedural step and cause the system to receive a projection image. Further, the projection image may be processed so as to determine a spatial position and orientation of at least the part of the object or of the robotic device.

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.

Systems and subsystems for cutting and stapling tissue 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, an articulation subsystem, a roll subsystem, and a transection subsystem that are operable independently of each other.

Disclosed are various real-time robotic-assisted dimension measurement systems and techniques based on the collected kinematic data from one or more surgical tools within a robotic surgical system. In some embodiments, the collected kinematic data can include positions and orientations of each joint of the one or more surgical tools which are derived from positions and orientations of a set of arm joints of one or more robotic arms which the one or more surgical tools are attached to. The disclosed dimension measurement systems allow a surgeon to perform real-time length measurements of both straight-lines and curved-lines, as well as area and volume measurements on specified portions of tissues or organs by strategically placing the tips of the one or more surgical tools over the tissues or organs, while viewing the distal ends of the surgical tools in a user display.

Systems and methods for surgical robotic navigation include multiple small surgical markers which avoid interfere with line of sight and do not otherwise disturb the surgical staff, while providing a convenient and highly accurate methodology for tracking and compiling the markers. Multi-arm robotic surgery systems are described in various embodiments that hold surgical tools and navigation cameras and optimally make use of several small surgical markers placed on patient anatomy of interest, surgical tools and the robotic arms. The small surgical markers are mathematically compiled so that the navigation cameras see a larger “compiled” surgical marker, thus providing greater accuracy.

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.

Systems and subsystems for cutting and stapling tissue 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 that includes a closure subsystem for a surgical instrument comprising a first closure input puck engageable with a first closure robotic output, a cam gear rotatably engaged with the first closure input puck, and a yoke pin coupled to a closure tube and movable from a first position to a second position in response to a rotation of the cam gear. Movement of the yoke pin from the first position to the second position translates the closure tube distally onto an anvil ramp of an anvil.

Systems and subsystems for cutting and stapling tissue are disclosed. More specifically, the present disclosure relates to systems, devices, and subsystems for attachments for robotic surgeries. The surgical instrument includes a transection subsystem comprising a rotatable shaft having a lumen, a firing rod extending at least partially through the lumen, a firing rack coupled to a proximal end of the firing rod, the firing rod being rotationally independent of the firing rack, and a firing gear engaged with the firing rack. Rotation of the firing gear moves the firing rack and the firing rod axially.

A robotic surgical system in which the system applies a scaling factor between user input from a user input device and corresponding movements of the robotic manipulator. Scaling factors may be applied or adjusted based on detected conditions such as the type of instrument being manipulated, detected distance between multiple instruments being manipulated, user biometric parameters.

The present disclosure relates to systems, devices, and subsystems for robotic surgeries. The surgical instrument is a robotic attachment that includes an articulation subsystem comprising a rotatable shaft, a distal channel retainer coupled to an end effector that is pivotable about an articulation pivot point, an articulation bushing slidable between a proximal position and a distal position, an articulation rod extending distally from the articulation bushing and coupled at a distal end to the distal channel retainer; and a rack movable with respect to the longitudinal axis of the rotatable shaft. Movement of the rack with respect to the longitudinal axis imparts an axial force onto the articulation bushing moving the articulation bushing between the proximal position and the distal position. Movement of the articulation bushing between the distal position and the proximal position actuates the articulation rod causing the distal channel retainer to pivot about the articulation pivot point.

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.

Systems and subsystems for cutting and stapling tissue are disclosed. More specifically, the present disclosure relates to systems, devices, and subsystems for attachments for robotic surgeries. The disclosed technology includes a housing for a surgical instrument configured to engage with a robotic arm. The housing comprises a first opening positioned to be engaged with at least a portion of a robotic arm, a second opening positioned proximate a rod extending from within the housing; and a fluid management system positioned within the housing proximate one of the first opening or the second opening, the fluid management system being configured to hold or divert fluid within the housing.

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.

Systems and subsystems for articulating 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 an articulation subsystem that moves independently of other subsystems that are operable independently of each other.

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 planning and assisting orthopaedic surgical procedures include a computer system and a robotic surgical device. The computer system receives multiple surgeon preferences, including target values and boundary values for surgical parameters of the orthopaedic surgical procedure. A surgeon uses the computer system to perform bony registration and leg-alignment registration for anatomy of a patient. The computer system determines a surgical plan for the orthopaedic surgical procedure based on the surgeon preferences, the bony registration, and the leg-alignment registration. The surgical plan includes planned values associated with the surgical parameters that are within the boundary values of the surgeon preferences. Determining the surgical plan may include automatically adjusting tibial coronal alignment, femoral coronal alignment, femoral flexion, femoral rotation, distal femoral resection height, proximal tibial resection height, and / or distal femoral resection height. The computer system may control the robotic surgical device according to the surgical plan.

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.