A sleep monitoring system includes an ECG device (2) and a respiration inductance plethysmogram (3) which monitor cardiac activity and physical (ribcage) respiration respectively and feed representative signals to a digital data processor. Operations (5-9) process the beat interval data, while in a second thread, operations (20-24) independently process the amplitude modulation of the ECG data caused by the respiratory motion of the subject. The inductance plethysmogram device (3) provides an input to the processor which represents respiration as directly monitored independently of the ECG. Operations (30-34) process this direct respiration data independently and in parallel, in a third thread. All extracted features are fed to a classifier which in step (10) combines selected combinations of features to make decisions in real time.

This document describes techniques and apparatuses enabling determination of health state trends for a consistent patient situation. Various noninvasive health monitors can be used to sense a patient's situation and health states, including disease progression, at those states. These noninvasive health monitors may also act passively and in a patient's normal course of life, which enhances many patient's desire to submit to monitoring, as well as increase consistency of use, as in many cases the patient does little or nothing to cause his or her health monitoring and health-trend determination. With health states determined for a consistent patient situation, more accurate and more robust health trends can be determined.

A device and method for sleep monitoring, in particular to a device and method for determining time-to-sleep and wake periods during sleep and to a device and method for determining rapid eye movement (REM) sleep and non REM (NREM) sleep. The method for determining time-obtaining motion data representative of motion of a user to-sleep and wake periods during sleep comprising the steps of obtaining motion data representative of motion of a user; detecting the time-to-sleep from the motion data based on a first time-above-threshold (TAT) threshold and a first proportional detecting the time-to-sleep from the motion data based integration method (PIM) threshold; and detecting on a first time-above-threshold (TAT) threshold and a the wake periods during sleep from the motion data first proportional integration method (PIM) threshold based on a second TAT threshold and a second PIM threshold.

Methods, techniques, apparatuses, and systems for setting up and tracking sleep consistency goals of users are provided. In one example, a computing system for setting a sleep schedule of a user of a biometric monitoring device may obtain sleep data derived from sensor data generated by the biometric monitoring device, store the sleep data in a sleep log data store as one or more sleep logs associated with an account assigned to the user, and calculate a target bedtime based on a scheduled waketime of the user and a sleep efficiency derived, at least in part, from the sleep data for one or more users stored in the sleep log data store. The computing system may also be configured to provide a number of personalized user interfaces to an individual for the purposes of setting a sleep schedule. Such interfaces may include parameters that are tailored to the individual sleep needs and/or characteristics of the individual's sleep.

This invention mainly discloses an EOG-based sleep staging method which is used to improve of an accuracy of automatic sleep judging result. The method may be executed by a processor and comprises steps of reading a to-be-test data having a variation depending on time of EOG generated by a user during a sleep process; acquiring a plurality of eye movement characteristics based on a variation of the EOG of a period, with the characteristics including an eye movement ratio, a blink count, a low frequency power ratio, a high frequency power ratio, an alpha rhythm ratio, a spindle rhythm ratio, a delta rhythm ratio and an average amplitude of eletrooculogram (EOG) signals; and determining a sleep state of the period is a “WAKE stage”, a “REM stage”, a “S1 stage”, a “S2 stage”, or a “SWS stage” based on the EOG characteristics. Furthermore, a computer readable medium with stored programs, and electronic apparatuses are provided.

An embodiment of a method for assessing cardiovascular disease in a user with a body region using a mobile computing device including a camera module, includes receiving a time series of image data of a body region of the user, the time series of image data captured during a time period; generating a photoplethysmogram dataset from the time series of image data; generating a processed PPG dataset; determining a cardiovascular parameter value of the user based on the processed PPG dataset; fitting a chronobiological model to (1) the cardiovascular parameter value, and (2) a subsequent cardiovascular parameter value, characterizing a cardiovascular parameter variation over time of the user based on the fitted chronobiological model; and presenting an analysis of the cardiovascular parameter variation to the user at the mobile computing device.

Methods and apparatus infer or indicate sleep stage(s) of a patient from a respiratory flow rate signal of the patient. The method may include applying a plurality of detection pathways to a signal representing a respiratory flow rate of the patient, wherein each detection pathway is configured to generate start events and end events indicating start times and end times of episodes respectively of a corresponding sleep stage, wherein each start event and each end event has a priority; and combining the start events and end events based on their priorities to produce an indication of the sleep stage of the patient. The apparatus may include a sensor configured to generate a signal representing a property of a flow of air within a patient interface; and a processor configured to implement a method of inferring a sleep stage of the patient from the signal.

The present disclosure generally relates to systems and methods for monitoring and/or the sleep stage of an individual using one or more sensors, and methods of treating medical conditions related thereto (e.g., obstructive sleep apnea).

Disclosed is a self-contained device for stimulating slow brain waves, capable of being worn by a person, in particular during a period of time when the person is sleeping. The device includes a supporting element, capable of surrounding the head of a person, and on which electrodes are mounted in contact with the person in order to acquire a measurement signal that represents a physiological electrical signal of the person; an acoustic transducer for emitting an acoustic signal stimulating the inner ear of the person; and on-board conditioning and control electronics for, in flexible real time, receiving the measurement signal and controlling the emission of an acoustic signal synchronized with a predefined slow brain wave time pattern.

The present disclosure describes a system configured to adjust the duration of individual sensory stimuli provided to a subject. The system is configured to determine a current amount of slow wave activity in the subject, responsive to the subject being presently in slow wave sleep, control one or more sensory stimulators to provide the individual sensory stimuli to the subject, determine habituation of the subject to the individual sensory stimuli and, responsive to the slow wave activity in the subject for a period of time following the providing of the individual sensory stimuli showing habituation, adjust the duration of the individual sensory stimuli.