A control method of an automatic compression circular anastomosis device, includes: correcting a zero point when an operation switch provided in a handle unit is turned on, by a control unit; controlling a motor to compress a tissue in a direction reaching a minimum distance at which a distance between a top surface of an anastomosis unit and a bottom surface of an anvil is minimized, by the control unit; measuring a real-time pressure applied to the tissue and a real-time distance between the top surface of the anastomosis unit and the bottom surface of the anvil in real-time, by the control unit; and controlling, when the real-time pressure and the real-time distance reach a set pressure and a set distance D.sub.r stored in advance, the anastomosis unit to cut unnecessary parts of the tissue and anastomose the tissue with a plurality of staples, by the control unit.

A surgical robot system includes a surgical robot having a robot base and a robot arm connected to the robot base. The surgical robot system further includes a joint manipulation arm configured to be attached to the robot arm and to be connected to an appendage of a patient and moved to apply force and/or torque to a joint connecting the appendage through movement of the robot arm. The surgical robot system further includes force and/or torque sensor apparatus configured to output a feedback signal providing an indication of an amount of force and/or torque that is being applied to the robot arm and/or the joint manipulation arm. At least one controller is configured to determine ligaments balancing at the joint based on a plurality of measurements of the feedback signal, and to output information characterizing the ligaments balancing.

A surgical robot system includes a surgical robot having a robot base and a robot arm connected to the robot base. The surgical robot system further includes a joint manipulation arm configured to be attached to the robot arm and to be connected to an appendage of a patient and moved to apply force and/or torque to a joint connecting the appendage through movement of the robot arm. The surgical robot system further includes force and/or torque sensor apparatus configured to output a feedback signal providing an indication of an amount of force and/or torque that is being applied to the robot arm and/or the joint manipulation arm. At least one controller is configured to determine ligaments balancing at the joint based on a plurality of measurements of the feedback signal, and to output information characterizing the ligaments balancing.

A system for robotic spinal manipulation includes a first robotic arm comprising an end effector; a second robotic arm configured to hold a spinal rod; at least one processor; and a memory storing instructions for execution by the at least one processor. The instructions, when executed, cause the at least one processor to control the first robotic arm to link the end effector with at least one vertebral screw implanted in a vertebra of a spine of a patient; control the second robotic arm to hold the spinal rod in a predetermined pose; and cause the first robotic arm to move the at least one implanted vertebral screw into engagement with the spinal rod.

Systems and methods for robotic retraction or robotic distraction are disclosed such as for a surgical procedure. An example system is a localization system to automatically position a trackable surgical retractor or distraction with respect to a patient comprising a patient tracking element adapted to be coupled to a patient; a processing unit configured to: track the poses of the patient via the patient tracking element, and the trackable surgical retractor or distractor; and command a robotic manipulator to move a tip of the trackable surgical retractor or distractor coupled to the manipulator from a first position, in engagement with the patient, to a second position while remaining in engagement with the patient.

A load sensing assembly for a spinal implant is disclosed. The load sensing assembly may include: a set screw having a drive interface, a lower cavity for receiving a cover, the cover including a protrusion that may engage with an anchoring member. The load sensing assembly may further include an antenna, and at least one sensor having an integrated circuit in communication with the antenna. In some embodiments, the integrated circuit is positioned within a sealed cavity of the set screw. In some embodiments, the antenna comprises a ferrite core and a plurality of windings that are oriented laterally with respect to a longitudinal axis of the set screw. In some embodiments, the sealed cavity of the set screw is hermitically sealed, and the antenna may be mechanically isolated by a bellows or cylindrical can structure.

A surgical instrument for operating hip joint osteoarthritis in a human patient is provided. The hip joint comprises an acetabulum, being a part of the pelvic bone, and a caput femur, being the proximal part of the femoral bone. The surgical instrument is adapted to assist in the operating of the hip joint osteoarthritis from the abdominal side of the pelvic bone of said human patient.

A rotary torque releaseor for orthopedic surgery includes an output anvil and a hammer that is capable of imparting linear and rotary force on the anvil, The anvil may be moveable on a leadscrew element to alternately generate energy in an energy storage means and to move along the leadscrew element to torque release the anvil. A viscoelastic mechanism or a dampening mechanism is used to reduce the reflected force and or torque during operation of the rotary torque releaseor. High frequency axial movements by the torque releaseor obviate the need for a surgeon to provide an external push force on the torque releaseor in order to perform a successful surgical operation.

A method for adjusting the operation of a surgical instrument using machine learning in a surgical suite is disclosed.

For kinetic sizing, the dynamic torque to be provided by a robotic system may be based off of, in part, a maximum acceleration. Rather than trying to extract maximum acceleration from many samples, a relationship of velocity to acceleration from repetitive user inputs relative to a non-surgical target in different situations (e.g., accurate, fast, or balance tracing of the target movement) is established. The velocity for any given situation may be used to estimate the acceleration from the relationship. Rather than using many trajectory samples from many users, a synthetic trajectory may be used. The synthetic trajectory may be fit to user data while maintaining high-coverage properties for direction of movement for any given pose of the robot. Alternatively, a virtual trajectory decoupled from time is used. The virtual trajectory samples the directions at any given pose in a global high-coverage manner, without specifically using a time-dependent sequence of poses.