A system for monitoring biometric signals of a user comprising: a garment configured to be worn by the user and comprising a mounting module having an array of connection regions; a set of biometric sensors coupled to the garment and configured to communicate with the array of connection regions to receive and transmit biometric signals indicative of muscle activity of the user; and a portable control module configured to couple to the garment in a first configuration and to decouple from the garment in a second configuration and comprising: a housing comprising an array of openings; a set of contacts, each including a first region that seals at least one of the array of openings and couples to at least one of the array of connection regions in the first configuration, and an electronics subsystem coupled to the housing and in communication with a second region of each contact.

One or both of epilepsy seizure detection and prediction at least by performing the following: running multiple input signals from sensors for epilepsy seizure detection through multiple classification models, and applying weights to outputs of each of the classification models to create a final classification output. The weights are adjusted to tune relative output contribution from each classifier model in order that accuracy of the final classification output is improved, while power consumption of all the classification models is reduced. One or both of epilepsy seizure detection and prediction are performed with the adjusted weights. Another method uses streams from sensors for epilepsy seizure detection to train and create the classification models, with fixed weights once trained. Information defining the classification models with fixed weights is communicated to wearable computer platforms for epilepsy seizure detection and prediction. The streams may be from multiple people and applied to an individual person.

An analysis device according to the present invention includes a memory, and processing circuitry coupled to the memory and configured to analyze data indicating a biosignal by using a predetermined analysis technique and an updated parameter corresponding to the predetermined analysis technique every time the parameter is updated, control a display to display an analysis result obtained together with an interface capable of changing display modes in response to user's operation, and update the parameter based on change in the display modes for the interface.

A device includes an EMG processing application operable with a processing module to receive an output signal from EMG testing, wherein the output signal represents electrical activity of at least one muscle. The EMG processing application is operable to process the output signal to detect at least one type of waveform of a plurality of types of waveforms from the output signal and display the detected at least one type of waveform.

A device includes an EMG processing application operable with a processing module to receive an output signal from EMG testing, wherein the output signal represents electrical activity of at least one muscle. The EMG processing application is operable to process the output signal to detect at least one type of waveform of a plurality of types of waveforms from the output signal and display the detected at least one type of waveform.

Systems and methods for managing sleep quality of a patient, comprising: collecting physiological signal data of the patient using a data acquisition unit electrically coupled to at least one sensor affixed to the patient that generates the physiologic signal data; using one or more hardware processors executing instructions stored in a storage device: filtering the physiological signal data into a plurality of frequency bands corresponding to a plurality of power spectra waveforms; and characterizing an etiology of sleep quality of the patient based on a comparison of at least a first power spectra waveform of the plurality of power spectra waveforms against at least a second power spectra waveform of the plurality of power spectra waveforms, wherein the sleep quality of the patient is managed based on the characterized etiology of sleep.

Systems and methods for managing sleep quality of a patient, comprising: collecting physiological signal data of the patient using a data acquisition unit electrically coupled to at least one sensor affixed to the patient that generates the physiologic signal data; using one or more hardware processors executing instructions stored in a storage device: filtering the physiological signal data into a plurality of frequency bands corresponding to a plurality of power spectra waveforms; and characterizing an etiology of sleep quality of the patient based on a comparison of at least a first power spectra waveform of the plurality of power spectra waveforms against at least a second power spectra waveform of the plurality of power spectra waveforms, wherein the sleep quality of the patient is managed based on the characterized etiology of sleep.

A mechanical ventilation system comprises a plurality of ventilation therapy sub-systems. Each of the ventilation therapy sub-systems is adapted to assist a respiratory function of the patient. The system also comprises a detector of the respiratory drive of the patient, an operator interface receiving one or more control parameters, and a main controller. The main controller assigns a therapeutic contribution to each of the ventilation therapy sub-systems based on the respiratory drive of the patient and on the control parameters. The controller modulates the respiratory drive of a patient by controlling each of the plurality of the ventilation therapy sub-systems according to its assigned therapeutic contribution. Distinct ventilation therapy sub-systems may apply negative pressure on the abdomen of the patient, deliver a non-pressurizing inspiratory flow to the patient, or induce a positive pressure in the airways of the patient.

A psychological health monitoring system according to an embodiment of the present disclosures includes a smart cup and a terminal. In the psychological health monitoring system, a user's biometric information is collected through a plurality of biosensors, and the user's current state is analyzed and determined on the basis of the collected biometric information, so as to display the user's psychological health/intoxication state through light or sound, so the user can check a psychological health/intoxication state depending on a beverage the user drinks and then correct drinking habits according to the psychological health/intoxication state to maintain good health.

A psychological health monitoring system according to an embodiment of the present disclosures includes a smart cup and a terminal. In the psychological health monitoring system, a user's biometric information is collected through a plurality of biosensors, and the user's current state is analyzed and determined on the basis of the collected biometric information, so as to display the user's psychological health/intoxication state through light or sound, so the user can check a psychological health/intoxication state depending on a beverage the user drinks and then correct drinking habits according to the psychological health/intoxication state to maintain good health.