In example implementations, an apparatus is provided. The apparatus includes a biometric sensor, a motion sensor, and a housing. The biometric sensor is to collect biometric data. The motion sensor is to detect movement of a finger of a user that is translated into motion or a control input in a virtual reality (VR) application. The housing is to enclose the biometric sensor and the motion sensor. The housing includes a mechanical coupling to attach to the finger of the user.

In example implementations, an apparatus is provided. The apparatus includes a biometric sensor, a motion sensor, and a housing. The biometric sensor is to collect biometric data. The motion sensor is to detect movement of a finger of a user that is translated into motion or a control input in a virtual reality (VR) application. The housing is to enclose the biometric sensor and the motion sensor. The housing includes a mechanical coupling to attach to the finger of the user.

A nerve integrity monitoring device includes a control module and a physical layer module. The control module is configured to generate a payload request. The payload request (i) requests a data payload from a sensor in a wireless nerve integrity monitoring network, and (ii) indicates whether a stimulation probe device is to generate a stimulation pulse. The physical layer module is configured to (i) wirelessly transmit the payload request to the sensor and the stimulation probe device, or (ii) transmit the payload request to a console interface module. The physical layer module is also configured to, in response to the payload request, (i) receive the data payload from the sensor, and (ii) receive stimulation pulse information from the stimulation probe device. The data payload includes data corresponding to an evoked response of a patient. The evoked response is generated based on the stimulation pulse.

A nerve integrity monitoring device includes a control module and a physical layer module. The control module is configured to generate a payload request. The payload request (i) requests a data payload from a sensor in a wireless nerve integrity monitoring network, and (ii) indicates whether a stimulation probe device is to generate a stimulation pulse. The physical layer module is configured to (i) wirelessly transmit the payload request to the sensor and the stimulation probe device, or (ii) transmit the payload request to a console interface module. The physical layer module is also configured to, in response to the payload request, (i) receive the data payload from the sensor, and (ii) receive stimulation pulse information from the stimulation probe device. The data payload includes data corresponding to an evoked response of a patient. The evoked response is generated based on the stimulation pulse.

A console for medical diagnosis includes a chair, a computer for displaying and communicating test results, various testing areas for performing multiple diagnostic tests, various testing devices including at least an EEG testing device, an ECG testing device, a BMD testing device, an ultrasonography testing device, and an EMG testing device, and openings for kidney probes and an echocardiogram probe. The testing areas include a first area for performing diagnostic tests on the head, a second area for performing diagnostic tests on sensory, a third area for performing diagnostic tests on the chest region, a fourth area for performing diagnostic tests on the pelvic and chest regions, a fifth area for performing diagnostic tests on blood, tissue, and bodily fluids, a sixth area for performing electromyographical tests, a seventh area for performing bone-related diagnostic tests, and an eighth area for performing diagnostic tests related to physical parameters and vitals.

A system and related methods for performing nerve detection during surgical access using ultrasound testing during surgery.

A system and related methods for performing nerve detection during surgical access using ultrasound testing during surgery.

A system and method for declaring arrhythmias in cardiac activity are provided. The system includes memory to store specific executable instructions and a machine learning (ML) model. One or more processors are configured to execute the specific executable instructions to obtain device classified arrhythmia (DCA) data sets generated by an implantable medical device (IMD) for corresponding candidate arrhythmias episodes declared by the IMD. The DCA data sets include cardiac activity (CA) signals for one or more beats sensed by the IMD and one or more device documented (DD) markers that are generated by the IMD. The system applies the ML model to the DCA data sets to identify a valid sub-set of the DCA data sets that correctly characterize the corresponding CA signals and to identify an invalid sub-set of the DCA data sets that incorrectly characterize the corresponding CA signals. The system includes a display configured to present information concerning at least one of the valid sub-set or invalid sub-set of the DCA data sets.

A system and method for declaring arrhythmias in cardiac activity are provided. The system includes memory to store specific executable instructions and a machine learning (ML) model. One or more processors are configured to execute the specific executable instructions to obtain device classified arrhythmia (DCA) data sets generated by an implantable medical device (IMD) for corresponding candidate arrhythmias episodes declared by the IMD. The DCA data sets include cardiac activity (CA) signals for one or more beats sensed by the IMD and one or more device documented (DD) markers that are generated by the IMD. The system applies the ML model to the DCA data sets to identify a valid sub-set of the DCA data sets that correctly characterize the corresponding CA signals and to identify an invalid sub-set of the DCA data sets that incorrectly characterize the corresponding CA signals. The system includes a display configured to present information concerning at least one of the valid sub-set or invalid sub-set of the DCA data sets.

A system and method for identifying a stimulation location on a nerve is disclosed. The system includes an image-based navigation interface used to facilitate advancing a stimulation element within a patient body toward a target nerve stimulation site. Using the system one determines, separately for each potential target nerve stimulation site, a neuromuscular response of muscles produced upon applying a stimulation signal at the respective separate potential target stimulation sites. The image-based navigation interface is configured to display a graphic identification of which muscles were activated for each respective potential target nerve stimulation site upon applying the stimulation signal.