A regionally integrated emergency stroke unit includes an information interaction area, an imaging examination area, and a thrombolytic therapy area. A doctor workstation, a comprehensive information surveillance monitor, and a process support artificial intelligence (AI) assistant are set in the information interaction area. A test device, a first television display, a movable low-field magnetic resonance imager, and an AI-assisted decision-making system are set in the imaging examination area. The process support AI assistant performs, via voice interaction or touchscreen keying interaction, automatic inquiry and auxiliary nervous system scale scoring, and further provides real-time retrieval support for a knowledge base and a clinical guideline. The AI-assisted decision-making system is configured to assist in decision-making based on an automatic inquiry result, a scale score result, the test result, and magnetic resonance imaging results of the head and neck, to generate and display a therapy regimen.

A system can perform image capture during a medical procedure. The system can record video from one or more video sources. The system can store the recorded video in a cached memory as stored video. The system can receive a triggering event, such as receiving a signal, operation of an actuator, or issuance of a voice command. In response to the triggering event, the system can capture a video segment from the stored video. Because the video segment is captured from stored video, the video segment can optionally include video and/or frames that occurred before the triggering event is received.

A training apparatus has an input device and a wearable computing device with a bio-signal sensor and a display to provide an interactive virtual reality (VR) environment for a user. The bio-signal sensor receives bio-signal data from the user. The user interacts with content that is presented in the VR environment. The user interactions and bio-signal data are scored with a user state score and a performance scored. Feedback is given to the user based on the scores in furtherance of training. The feedback may update the VR environment and may trigger additional VR events to continue training.

A handling device for handling a medical and/or surgical instrument, includes a multi-joint robot arm, which at its distal end carries an instrument holder designed for holding a medical and/or surgical instrument, and a control device, which is designed at least to control the multi-joint robot arm, wherein the handling device includes a speech detection device with at least one microphone, which is arranged in a region of the distal end of the multi-joint robot arm or integrated therein and is designed to detect at least a voice of a user of the handling device.

A system can perform image capture during a medical procedure. The system can record video from one or more video sources. The system can store the recorded video in a cached memory as stored video. The system can receive a triggering event, such as receiving a signal, operation of an actuator, or issuance of a voice command. In response to the triggering event, the system can capture a video segment from the stored video. Because the video segment is captured from stored video, the video segment can optionally include video and/or frames that occurred before the triggering event is received.

A method of facilitating a surgical procedure includes receiving a first input including a first surgical article type and a first quantity of the first surgical article type for surgical articles that have been counted in to the procedure, displaying an electronic count including the first surgical article type and the first quantity of the first surgical article type, and receiving a subsequent input to alter the count. The method further includes capturing, with a microphone, speech including a verbal count for the surgical articles that have been counted in to the procedure, converting the verbal count into machine-encoded values including a second surgical article type and a second quantity, and comparing the electronic count to the machine-encoded values to identify a discrepancy. The method further includes displaying the identified discrepancy.

Systems, methods and devices for surgical procedurelization via a modular energy system are disclosed herein. In various aspects, the systems, methods and devices include an energy module, a header module communicably coupled to the energy module, and a display screen capable of rendering a graphical user interface (GUI). The GUI may be configured to display a plurality of steps that correspond with actions performed by a user while operating the modular energy system. In some aspects, the steps displayed are steps of a predetermined procedural checklist corresponding with a mental model followed by the user while performing a surgical procedure. In some aspects, the steps displayed are steps of an output verification process.

One or more example embodiments provides a method for speech control of a medical apparatus, a corresponding speech control apparatus, a medical system comprising the speech control apparatus, a computer program product and a computer-readable storage medium.

A system and method for operating a touchscreen of a gas-enhanced electrosurgical generator. The generator has a display module and a primary controller. The display module has a plurality of touch sensors, a PCB power relay and a CPU. The method comprises selecting electrosurgery settings through a graphical user interface, activating through an input device plasma delivery from the gas-enhanced electrosurgical generator, disabling the plurality of touch sensors through software running on the primary controller, disconnecting power from the plurality of touch sensors with the PCB power relay in response to the disabling of the plurality of touch sensors, applying power to an electrode in the plasma accessory connected to the gas-enhanced electrosurgical generator, and de-activating through an input device plasma delivery from the gas-enhanced electrosurgical generator to the plasma accessory connected to the gas-enhanced electrosurgical generator.

Embodiments of the present application provide a method and apparatus for controlling a medical device, and a medical system. The method includes receiving a speech instruction from a sound pickup apparatus, inputting the speech instruction into a deep learning neural network, and, on the basis of the deep learning neural network, outputting an instruction for controlling the medical device, and controlling movement of the medical device according to the instruction. Therefore, by means of AI/ML-based speech control, the medical device can be accurately controlled without assistance of multiple people, which can reduce labor costs, improve efficiency, and reduce the risk of surgery failing.