In an embodiment, an electrogram (EGM) processing system provides, for display by a head-mounted display (HMD) worn by a user, a holographic rendering of intracardiac geometry. The HMD also displays an electrogram waveform. The EGM processing system determines a gaze direction of the user by processing sensor data from the HMD. The HMD displays a marker overlaid on the electrogram waveform at a location based on an intersection point between the gaze direction and the electrogram waveform. The EGM processing system determines a measurement of the electrogram waveform using the location of the marker. The HMD displays the measurement of the electrogram waveform.

The present application relates to a motion control method and system for a mechanical arm and surgical system, the terminal end of the mechanical arm is adapted to carry an effector, the method includes steps of: receiving a first control command from a first input device by a graphical user interface, wherein the first control command is configured to control the mechanical arm to move according to a first movement mode; receiving a second control command from the first input device or a second input device, wherein the second control command is configured to control the mechanical arm to enter a second movement mode; and receiving a third control command from the second input device, wherein the third control command is configured to control the effector to perform a predetermined movement, wherein the first input device and the second input device are separated from each other.

A surgical instrument comprises a housing and a valve mounted in the housing. The valve is configured to control a flow of a fluid into or out of a surgical site in response to either a robotic actuation of the valve or a manual actuation of the valve. The valve comprises a valve shaft, a receiving member structurally coupled to the valve shaft, and a manual actuation component structurally coupled to the valve shaft and extending from the housing. The receiving member is configured to releasably couple to a driver of a robotic manipulator to receive the robotic actuation from the driver remotely controlled by a surgeon to adjust a state of the valve. The manual actuation component is configured to receive the manual actuation to adjust the state of the valve.

A method for adjusting the operation of a surgical instrument using machine learning in a surgical suite is disclosed. The method comprises the steps of gathering data during surgical procedures, wherein the surgical procedures include the use of a surgical instrument, analyzing the gathered data to determine an appropriate operational adjustment of the surgical instrument, and adjusting the operation of the surgical instrument to improve the operation of the surgical instrument.

A computer assisted surgery system comprising: a computerised surgical apparatus; and a control apparatus; wherein the control apparatus comprises circuitry configured to: receive information indicating a first region of a surgical scene from which information is obtained by the computerised surgical apparatus to make a decision; receive information indicating a second region of the surgical scene from which information is obtained by a medical professional to make a decision; determine if there is a discrepancy between the first and second regions of the surgical scene; and if there is a discrepancy between the first and second regions of the surgical scene: perform a predetermined process based on the discrepancy.

A computer assisted surgery system comprising an image capture apparatus, a display, a user interface and circuitry, wherein the circuitry is configured to: receive information indicating a surgical scenario and a surgical process associated with the surgical scenario; obtain an artificial image of the surgical scenario; output the artificial image for display on the display; receive permission information via the user interface indicating if there is permission for the surgical process to be performed if the surgical scenario is determined to occur.

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.

Systems, methods, and instrumentalities are disclosed for switching a control scheme to control a set of system modules and/or modular devices of a surgical hub. A surgical hub may determine a first control scheme that is configured to control a set of system modules and/or modular devices. The surgical hub may receive an input from one of the set of modules or a device located in an OR. The surgical hub may make a determination that at least one of a safety status level or an overload status level of the surgical hub is higher than its threshold value. Based on at least the received input and the determination, the surgical hub may determine a second control scheme to be used to control the set of system modules. The surgical hub may send a control program indicating the second control scheme to one or more system modules and/or modular devices.

A control device (1) for an electrosurgical instrument (2), in particular a high-frequency sealing instrument, including a fixed handle part (3), a movable handle part (4), an activation element (5) for activating a current flow, in particular a first type, preferably a sealing current, wherein the activation element (5) is or can be adjusted between a deactivation position and at least one activation position when the movable handle part (4) is actuated, wherein, when the movable handle part (4) is actuated, the activation element (5) is or can be adjusted about an axis of rotation (7).

A method for characterizing a state of an end effector of an ultrasonic device is disclosed. The ultrasonic device including an electromechanical ultrasonic system defined by a predetermined resonant frequency. The electromechanical ultrasonic system further including an ultrasonic transducer coupled to an ultrasonic blade. The method including applying, by an energy source, a power level to the ultrasonic transducer; measuring, by a control circuit coupled to a memory, an impedance value of the ultrasonic transducer; comparing, by the control circuit, the impedance value to a reference impedance value stored in the memory; classifying, by the control circuit, the impedance value based on the comparison; characterizing, by the control circuit, the state of the electromechanical ultrasonic system based on the classification of the impedance value; and adjusting, by the control circuit, the power level applied to the ultrasonic transducer based on the characterization of the state of the end effector.