Closed-loop sleep management method, head-worn closed-loop sleep management system, and electronic device

Abstract

A closed-loop sleep management method applied to a head-worn closed-loop sleep management device includes: performing sleep monitoring in real time based on an electroencephalogram (EEG) signal, an electrooculogram (EOG) signal, a heart rate (HR), and a blood oxygen saturation (SpO2); and controlling an intervention component to perform sleep intervention when a sleep monitoring result meets a preset condition. The sleep monitoring includes sleep staging and calculation of a duration of a current sleep stage. The sleep monitoring result includes the current sleep stage and the duration thereof. The method applies a deep learning algorithm to perform sleep staging and calculate the duration of the current sleep stage based on multi-modal signals, enabling real-time and accurate sleep state monitoring. Additionally, the method can achieve effective dynamic sleep intervention based on the sleep monitoring result, achieving closed-loop management from sleep monitoring to sleep intervention.

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