A method and system for evaluating sleep quality based on skin electricity

Abstract

The invention relates to the field of sleep assessment and especially relates to a method and system for sleep quality assessment based on galvanic skin responses. The method comprises the steps that galvanic skin motion data during sleep duration of a human body is acquired; preset galvanic skin fluctuation indicators are extracted in the galvanic skin motion data, wherein the galvanic skin fluctuation indicators comprise the quantity of galvanic skin fluctuation vibrations and duration of the galvanic skin fluctuation vibrations; a sleep score is obtained according to the galvanic skin fluctuation indicators; and sleep quality is assessed according to a preset sleep assessment system and the sleep score, and an assessment result is returned. According to the invention, the galvanic skin fluctuation indicators are extracted through analysis of the galvanic skin motion data; correlation between the galvanic skin fluctuation indicators and the sleep quality is established; and the sleep quality is assessed. In this way, the sleep quality of the human body is quantized accurately and effectively according to the assessment result.

Description

technical field [0001] The invention relates to the field of sleep assessment, in particular to a method and system for assessing sleep quality based on skin electricity. Background technique [0002] As an indispensable life activity in daily life, sleep is closely related to the basic operation of the human body, including normal growth, physical recovery, emotional regulation, and memory organization. Sufficient sleep is the basis for maintaining human mental and physical health, while insufficient sleep is harmful to human health and increases the risk of disease invasion. Therefore, the quality of daily sleep will be related to all aspects of people's lives, and timely acquisition of their own sleep quality and actively taking measures to adjust it has become a hot spot of concern. Sleep analysis has traditionally been based primarily on brain waves. Human sleep stages include NREM (NON-RAPID EYE MOVEMENT, slow eye movement period) and REM (RAPID EYE MOVEMENT, rapid e...

AI Technical Summary

Problems solved by technology

Human sleep stages include NREM (NON-RAPID EYE MOVEMENT, slow eye movement period) and REM (RAPID EYE MOVEMENT, rapid eye movement period). The sleep stage can be identified through brain waves to obtain sleep quality, but brain waves need Monitored by EEG equipment, which is not portable and expensive, so it has been difficult to be widely used

In addition, there are sensors that collect data such as body temperature and heart rate during sleep for sleep analysis and quality assessment. However, there are large individual differences in data such as body temperature and heart rate during sleep, which will also lead to low final accuracy.

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