Research On Distributed Sleep Monitoring System Based On Internet Of Things

In recent years,people have paid more and more attention to sleep health.Sleep problems such as sleep apnea syndrome have become a major hidden danger to health because they are difficult to detect by patients themselves.Traditional sleep monitoring requires professional equipment in the hospital for monitoring.Due to the limitations of the equipment's large size,complicated operation,and expensive price,it cannot be widely spread to nursing homes,community health centers and other places.Therefore,it is necessary to develop a low-cost,simple operation,small size and easy-to-manage sleep monitoring equipment system.The distributed sleep monitoring system based on the Internet of Things designed and implemented in this article supplements the application scenarios of sleep monitoring.This paper designs and studies a distributed sleep monitoring system based on the Internet of Things.In this system,the physiological signals are collected by flexible sensors,separated the physiological signals into several potential components by algorithm.The potential components are used to reconstruct the respiratory signals and BCG signals.Then the effective physiological signals are used to analyze the abnormal sleep conditions.The system uses the way of subscription and release to monitor the sleep status of the testers.The main contents of this paper are as follows:1.Design of hardware system.Including signal acquisition,acquisition,filtering,transmission and other processes.Reduce costs on the basis of obtaining pure raw physiological signals.2.Decomposition and reconstruction of physiological signals.The variational modal decomposition method is used to decompose the physiological signals.Compare the decomposition effects of empirical mode decomposition and complementary ensemble empirical mode decomposition.According to the characteristics of the physiological signals obtained by decomposition,adaptive methods were used to reconstruct the respiratory signals and BCG signals.The reconstruction effects based on empirical mode decomposition,complementary set empirical mode decomposition and variational mode decomposition are compared.3.Identification of abnormal conditions.A sleep apnea detection method is designed according to the characteristics of sleep apnea.4.Engineering implementation of a distributed sleep monitoring system based on the Internet of Things.Including the construction of the Internet of Things platform,the engineering implementation of each link in the system,the development of the host computer,the development of the IOS mobile client.