Sensing, computing and intervention for sleep health

Abstract

<p indent=0mm>As an instinctive part of human life, sleep not only is of great significance to the individual’s physical and mental health, but also could be a natural means of regulating, restoring and enhancing body functions. Accordingly, sleep quality not only affects people’s quality of life, but also is closely related to the occurrence and development of many physiological and psychological diseases. Statistics show that about one-third of the population in China has sleep disorders, and a growing number of people have sleep health requirements. There is a prominent contradiction between this demand and the backward daily sleep health management. Therefore, it is urgent to set up theories and methods ranging from sleep structure conversion mechanism to sleep quality monitoring and intervention. For this reason and based on the discussion of the Y5th Xiangshan Scientific Conference (Smart Sensing and Computing for Sleep Health), this paper provides an in-depth analysis of sleep perception, intelligent sleep computing and sleep intervention methods in recent years. It foresees the key scientific and technical issues in the three stages of this closed-loop system. Combining wearable sensing and medical artificial intelligence technology, we should form a platform and develop algorithms from sleep quality monitoring to objective diagnosis of sleep disorders. Principles and methods of physical and behavioral interventions should be also explored to improve the physical and mental state of sleep regulation, so as to establish a new paradigm of “active sleep health” comprehensively. Considering the feasibility of the next few years from the perspective of principle, mechanisms, methods and measures, we propose the following recommendations: (1) Sleep-wake transformation mechanism. The study of sleep-related electrophysiology biomarkers could reveal the sleep-wake transformation and regulatory mechanisms to guide the development of sleep health standards for the Chinese population. Based on such a mechanism, an objective assessment of people’s overall health status could be achieved. It will be used for national sleep health screening and prevention of sleep disorders, and provide a theoretical basis for active sleep health promotion. (2) Sleep health promotion for specific populations. In order to adapt to the sleep health of children, youth, elderly and special types of personnel, research on the brain neural mechanism of biological rhythm should be carried out for different groups in order to build personalized multi-physiological parameter monitoring devices, intelligent analysis algorithms and active intervention paradigms. (3) Sleep health promotes physical and mental health. Sleep is closely related to the development of many physiological diseases. To reduce the incidence of chronic diseases, we should explore the mechanism of its association with the cardiovascular system, respiratory system, nervous system and endocrine system. A multimodality data analysis system could be developed with independent intellectual property rights. This will promote the advancement of sleep-related industries in China and propose relevant technical standards and guidelines to achieve active health management.