A surgical system includes a robotic device, a surgical tool mounted on the robotic device, and a processing circuit. The processing circuit is configured to receive image data of an anatomy, generate a virtual bone model based on the image data, identify a soft tissue attachment point on the virtual bone model, plan placement of an implant based on the soft tissue attachment point, generate a control object based on the placement of the implant, and control the robotic device to confine the surgical tool within the control object.

A robotic surgical system comprises a surgical tool, a manipulator configured to support the surgical tool, a force/torque sensor to measure forces and torques applied to the surgical tool, and a control system. The control system obtains a three-dimensional milling path for the surgical tool. The control system also receives one or more signals from the force/torque sensor in response to a user manually applying user forces and torques to the surgical tool. The control system determines a commanded pose to which to command the manipulator to advance the surgical tool along the milling path based on a tangential component of the user forces and torques, based on a virtual simulation using virtual constraints, and/or based on other suitable factors to promote guided, manual movement of the surgical tool along the milling path.

Methods, systems and devices for pre-operatively planned shoulder surgery guides and implants. Pre-operative planning methods for designing glenoid placement guides and depth-control pins based on considerations of multiple factors affecting the outcome of shoulder surgery. Methods of using surgery guides and implants, including glenoid placement guides and depth-control pins, in patients undergoing shoulder surgery.

A surgical system includes an arm extending from the base and having a distal end configured to be coupled to a tool, a first marker coupled in fixed relation to the base, and a tracking system. The tracking system is configured to collect first data indicative of a position of the first marker and collect second data indicative of a position an anatomical feature of a patient. The surgical system also includes a processor configured to calculate a position of the tool relative to the anatomical feature based on the first data and the second data.

The disclosure describes examples of machine-learned model based techniques. A computing system may obtain patient characteristics of a patient and implant characteristics of an implant. The computing system may determine information indicative of an operational duration of the implant based on the patient characteristics and the implant characteristics and output the information indicative of the operational duration of the implant. In some examples, one or more processors may be configured to receive, with a machine-learned model of the computing system, implant characteristics of an implant to be manufactured, apply model parameters of the machine-learned model to the implant characteristics, determine information indicative of dimensions of the implant to be manufactured based on the applying of the model parameters of the machine-learned model, and output the information indicative of the dimensions of the implant to be manufactured.

A system for assessing laxity of a joint of a patient is disclosed. The system comprises a tensioner tool having a substantially rigid portion that may be inserted within the joint to apply a force against a bone surface thereof. The system further comprises a tensioner sock having a flexible body with an opening to receive the tensioner tool and a sensor array disposed on the flexible body. Each sensor of the sensor array is configured to contact the bone surface and detect a pressure when the force is applied against the bone surface. The system further comprises a processor configured to receive the detected pressure from each sensor and calculate the force applied to the bone surface based on the detected pressures.

A spinal correction rod implant manufacturing process includes: estimating a targeted spinal correction rod implant shape based on a patient specific spine shape correction and including spine 3D modeling, one or more simulation loops each including: first simulating an intermediate spinal correction rod implant shape from modeling mechanical interaction between the patient specific spine and: either, for the first simulation, the implant shape, or, for subsequent simulation, if any, an overbent implant shape resulting from the previous simulation loop, a second simulation of an implant shape overbending applied to the targeted spinal correction rod implant shape producing an overbent spinal correction rod implant shape representing a difference between: either, for the first loop, the targeted spinal correction rod implant shape, or, for subsequent loop, if any, the overbent spinal correction rod implant shape resulting from the previous simulation loop, and the intermediate spinal correction rod implant shape.

The present application provides an automatic knife stop device and a system for fibula cutting, a computer equipment, and a medium. The device includes: an acquisition module; a threshold module; and a judgment module. The present application can avoid the destruction of blood vessels during shaping and greatly improve the success rate of surgery, while greatly improve the robustness of the control system by increasing the strength of the force feedback signal.

Systems and methods for generating patient-specific surgical guides comprising: capturing a first and second images of an orthopedic element in different reference frames using a radiographic imaging technique, detecting spatial data defining anatomical landmarks on or in the orthopedic element using a neural network, applying a mask to the orthopedic element defined by an anatomical landmark, projecting the spatial data from the first image and the second image to define volume data, applying the neural network to the volume data to generate a reconstructed three-dimensional (“3D”) model of the orthopedic element; and calculating dimensions for a patient-specific surgical guide configured to abut the orthopedic element.

Systems and methods for planning and performing image free implant revision surgery are discussed. For example, a method for generating a revision plan can include collecting pre-defined parameters characterizing a target bone, generating a 3D model, collecting a plurality of surface points, and generating a reshaped 3D model. Generating the 3D model of the target bone can be based on a first portion of the pre-defined parameters. Generating the reshaped 3D model can be done based on the plurality of surface points collected from a portion of the surface of the target bone.