Methods, apparatus, and systems relating to a Wearable Cardioverter Defibrillator (WCD) system capable of logging event data and/or broadcasting state changes and/or system status information to external clients are described. In an embodiment, a processor stores data corresponding to one or more event markers in memory in response to occurrence of an event. Occurrence of the event is detected based at least in part on detection of one or more parameters by one or more sensors or a signal to be generated by one or more of electrodes of the WCD system. A communication device transmits at least a portion of the stored data to a remote device. A patient condition or a WCD system condition can then be detected based at least in part on analysis of the stored data and/or the transmitted portion of the stored data.

Methods, apparatus, and systems relating to a Wearable Cardioverter Defibrillator (WCD) system capable of logging event data and/or broadcasting state changes and/or system status information to external clients are described. In an embodiment, a processor stores data corresponding to one or more event markers in memory in response to occurrence of an event. Occurrence of the event is detected based at least in part on detection of one or more parameters by one or more sensors or a signal to be generated by one or more of electrodes of the WCD system. A communication device transmits at least a portion of the stored data to a remote device. A patient condition or a WCD system condition can then be detected based at least in part on analysis of the stored data and/or the transmitted portion of the stored data.

A system includes a collar that is worn around a neck of the user. A stimulator is coupled to the collar such that the stimulator is positioned adjacent to an airway of the user. The sensor is coupled to the collar and configured to generate data associated with the airway of the user. The memory is coupled to the collar and storing machine-readable instructions. The control system is coupled to the collar and includes one or more processors configured to execute the machine-readable instructions to determine, based at least on an analysis of the generated data, that the user is currently experiencing an apnea event. In response to the determination, the control system causes the stimulator to provide electrical stimulation, at a first intensity level, to one or more muscles of the user that are adjacent to the airway to aid in stopping the apnea event.

A method of processing the psychophysical state of a driver to improve the driving experience of road vehicle driven by a driver and comprising the steps of: cyclically detecting one or more objective vital parameters of the driver by means of one or more first sensors installed within a vehicular system; processing the value of a vital state index according to said one or more objective vital parameters detected; cyclically detecting one or more subjective parameters of the driver by means of one or more second sensors installed within the vehicular system; processing, starting from the objective vital parameters and according to the subjective parameters, the psychophysical state of the driver.

A method of processing the psychophysical state of a driver to improve the driving experience of road vehicle driven by a driver and comprising the steps of: cyclically detecting one or more objective vital parameters of the driver by means of one or more first sensors installed within a vehicular system; processing the value of a vital state index according to said one or more objective vital parameters detected; cyclically detecting one or more subjective parameters of the driver by means of one or more second sensors installed within the vehicular system; processing, starting from the objective vital parameters and according to the subjective parameters, the psychophysical state of the driver.

Embodiments of the disclosed subject matter generally relate to electrically grounding a user who may be working in an environment where static electricity might otherwise build up on the user and damage sensitive electronic devices being handled by the user. Embodiments include attaching an electrocardiogram (ECG) electrode to the user's skin and removably attaching the ECG electrode to an electrical conductor which may be detachably connected to a flexible base disposed on the outside of and under the user's shoe.

Embodiments of the disclosed subject matter generally relate to electrically grounding a user who may be working in an environment where static electricity might otherwise build up on the user and damage sensitive electronic devices being handled by the user. Embodiments include attaching an electrocardiogram (ECG) electrode to the user's skin and removably attaching the ECG electrode to an electrical conductor which may be detachably connected to a flexible base disposed on the outside of and under the user's shoe.

The detection and diagnosis of a variety of cardiovascular disorders and levels of heart condition, using a novel method and system, according to a comprehensive analysis of cardiac electrical signal via the frequency domain, time domain, spatial domain.

The detection and diagnosis of a variety of cardiovascular disorders and levels of heart condition, using a novel method and system, according to a comprehensive analysis of cardiac electrical signal via the frequency domain, time domain, spatial domain.

An artificial intelligence self-learning-based automatic electrocardiography analysis method and apparatus, the method comprising data preprocessing, heartbeat feature detection, interference signal detection and heartbeat classification based on deep learning, signal quality evaluation and lead combination, heartbeat verification, analysis and calculation of electrocardiography events and parameters, and finally automatic output of reporting data, realizing an automated analysis method having a complete and rapid flow. The automatic electrocardiography analysis method may also record modification information of an automatic analysis result, collect modified data, and feed same back to the depth learning model to continue training, thereby continuously making improvements and improving the accuracy of the automatic analysis method.