Distributed Sleep Monitoring System with Mobile Terminal

Siyuan Gao, Chang Liu, Anze Cheng, Xu Jiao
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Abstract

In this paper, a distributed multi-lead sleep monitoring system is designed. The hardware is divided into a pressure sensor array and an intelligent terminal. The pressure sensor array is responsible for collecting the ballistocardiogram signals of the human body and transmits it locally to the intelligent terminal for analysis and processing. The IoT module is embedded in the intelligent terminal, and the effect of remote monitoring can be achieved through the matching cloud service and software support. In order to avoid data redundancy in high concurrency scenarios, the system adopts a hierarchical processing scheme. The source pressure data is first analyzed in the intelligent terminal, and only the result data is uploaded. And equipped with a specific frame format to prevent user privacy from being tampered with during transmission. The multilead monitoring scheme of this system effectively avoids the situation of misalignment with the sensor caused by body movement during sleep. And taking into account the uncertainty of the network, a storage function is added to the smart terminal to realize the data retrieval in different places. After analysis and evaluation, the calculation time can be shorter than 600ms, which has good real-time performance. The average recognition rate of breathing under the condition of stable lying down was 95.438%, The average recognition rate of heartbeat is 97.1825%, which has a good application scenario.
基于移动终端的分布式睡眠监测系统
本文设计了一种分布式多导联睡眠监测系统。硬件分为压力传感器阵列和智能终端。压力传感器阵列负责采集人体的心电图信号,并将其本地传输到智能终端进行分析处理。物联网模块嵌入智能终端,通过配套的云服务和软件支持,实现远程监控的效果。为了避免高并发场景下的数据冗余,系统采用分层处理方案。首先在智能终端分析源压力数据,只上传结果数据。并配有特定的帧格式,防止用户隐私在传输过程中被篡改。该系统采用多导联监测方案,有效避免了因睡眠时身体运动导致与传感器错位的情况。并考虑到网络的不确定性,在智能终端上增加了存储功能,实现了异地数据检索。经分析评估,计算时间可短于600ms,具有较好的实时性。平躺状态下呼吸的平均识别率为95.438%,心跳的平均识别率为97.1825%,具有较好的应用场景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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