A system (101) for monitoring a physiological condition of a user (104) is disclosed herein. The system (101) includes a receiving module (110) configured to receive a plurality of short-term segments of Heart Rate Variability (HMI) (302) or short-term electrocardiogram (ECG) segments (402) or short voice recordings (602) from the user (104) recorded at different time points. The system includes a stitching module (114) for stitching the plurality of short-term segments and creating a stitched segment. The system further includes an extracting module (116) extracting feature from the stitched segment and a predicting module (118) for predict the physiological condition, based on the feature.

A method, apparatus, and computer program monitor a user's heart activity during a physical exercise. A heart activity measurement signal representing the user's heart activity is acquired and a phase component of the heart activity measurement signal is monitored. On the basis of the monitoring of the phase component, one or more actions are carried out.

A method, apparatus, and computer program monitor a user's heart activity during a physical exercise. A heart activity measurement signal representing the user's heart activity is acquired and a phase component of the heart activity measurement signal is monitored. On the basis of the monitoring of the phase component, one or more actions are carried out.

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 wearable device may include a sensor. The sensor may include a flexible fabric, a conjugated polymer coating deposited on the fabric via vapor-phase oxidative chemical vapor deposition (oCVD), and a plurality of electrodes in coupled to the conjugated polymer coating. The wearable device may further include a processor communicatively coupled to the electrodes. The processor may measure an electrical property across the electrodes, determine a physiological event based on the measured electrical property, and output measurement information corresponding the physiological event.

When evaluating the quality of photoplethysmography (PPG) signal (52) measured from a patient monitor (e.g., a finger sensor or the like), multiple features of the PPG signal are extracted and analyzed to facilitate assigning a score to the PPG signal or portions (e.g., heartbeats) thereof. Heartbeats in the PPG signal are segmented out using concurrently captured electrocardiograph (ECG) signal (50), and for each heartbeat, a plurality of extracted features are analyzed. If all extracted features satisfy one or more predetermined criteria for each feature, then the heartbeat waveform is compared to a predefined heartbeat template. If the waveform matches the template (e.g., within a predetermined match percentage or the like), then the heartbeat is classified as “clean.” If the heartbeat does not patch the template, or if one or more of the extracted features fails to satisfy its one or more pre-determined criteria, the heartbeat is classified as “noisy.”

When evaluating the quality of photoplethysmography (PPG) signal (52) measured from a patient monitor (e.g., a finger sensor or the like), multiple features of the PPG signal are extracted and analyzed to facilitate assigning a score to the PPG signal or portions (e.g., heartbeats) thereof. Heartbeats in the PPG signal are segmented out using concurrently captured electrocardiograph (ECG) signal (50), and for each heartbeat, a plurality of extracted features are analyzed. If all extracted features satisfy one or more predetermined criteria for each feature, then the heartbeat waveform is compared to a predefined heartbeat template. If the waveform matches the template (e.g., within a predetermined match percentage or the like), then the heartbeat is classified as “clean.” If the heartbeat does not patch the template, or if one or more of the extracted features fails to satisfy its one or more pre-determined criteria, the heartbeat is classified as “noisy.”

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.

A method includes a first acquisition step of acquiring exercise intensity of exercise done by a target person, a second acquisition step of acquiring an electrocardiographic waveform of the target person who does the exercise, a third acquisition step of acquiring a predetermined feature amount from the acquired electrocardiographic waveform, and an estimation step of estimating an AT of the target person based on a relationship between the predetermined feature amount and the acquired exercise intensity. The estimation step includes a step of estimating the AT of the target person based on exercise intensity corresponding to an inflection point in a change of the predetermined feature amount with respect to the acquired exercise intensity.

A method includes a first acquisition step of acquiring exercise intensity of exercise done by a target person, a second acquisition step of acquiring an electrocardiographic waveform of the target person who does the exercise, a third acquisition step of acquiring a predetermined feature amount from the acquired electrocardiographic waveform, and an estimation step of estimating an AT of the target person based on a relationship between the predetermined feature amount and the acquired exercise intensity. The estimation step includes a step of estimating the AT of the target person based on exercise intensity corresponding to an inflection point in a change of the predetermined feature amount with respect to the acquired exercise intensity.