Sleep monitoring method, device and equipment

Abstract

The invention discloses a sleep monitoring method, device and equipment. The method comprises the following steps: acquiring a GSR signal, a heart rate, blood oxygen and a body movement signal of a sleep state in a preset time period; performing feature extraction on the signal data by using an MRCNN neural network module and an AFR neural network module to obtain data with most distinctive features; analyzing and identifying the most distinctive feature data according to a sleep identification network model learned and trained in advance to obtain the probability that the corresponding sleep state is in four different sleep stages of an awakening stage, a rapid eye movement stage, a light sleep stage and a deep sleep stage in a preset time period; the sleep stage with the maximum probability is used as the corresponding sleep stage in the preset time period. According to the application, the GSR signal, the heart rate, the blood oxygen and the body movement signal of the testee are extracted through the MRCNN neural network module and the AFR neural network module to obtain the data with the most distinctive features, and accurate and effective monitoring of the sleep stage of the testee is realized.

Description

technical field [0001] The present invention relates to the field of medical technology, and in particular, to a sleep monitoring method, device and device. Background technique [0002] Sleep is one of the vital life activities of the human body, enabling the brain and body to recover from the fatigue accumulated from daily activities. As social competition brings more and more pressure to people's study, work and life, people of all ages have sleep problems. According to statistics, the number of people with sleep disorders in China has exceeded 300 million, and sleep disorders have become a social problem that has attracted much attention. [0003] Monitoring daily sleep quality can effectively provide critical feedback on human health and lifestyle. At present, the monitoring of human sleep status on the market mainly collects data such as the heart rate and blood oxygen of the detector, and then the medical staff roughly determines the sleep status of the monitored pe...

AI Technical Summary

Problems solved by technology

At present, the monitoring of human sleep status in the market is mainly to collect data such as the heart rate and blood oxygen of the tester, and then the medical staff can roughly determine the sleep status of the monitored person based on medical experience. Experience requirements are high, and the accuracy of monitoring results is poor

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