Alternative class III distributed polysomnography system

Abstract Introduction Impairment of sleep quality directly increases the risk of heart attack, obesity, and stroke, among other conditions, which makes polysomnography (PSG) an important public health tool. However, the inherent problems with PSG render the correct diagnosis of sleep diseases a difficult task. As a novel alternative to the class II PSG system, this work presents a distributed system composed of three modules, which together are capable of the simultaneous monitoring of environmental variables and patient signals. This system could reduce the distress of a PSG exam in certain cases, dismiss the need for an overnight sleep in a healthcare/sleep centre, and facilitate self-setup and internet-based diagnosis. Methods Hardware and software capable of synchronously monitoring, processing and logging into a µSD card environmental parameters (temperature, humidity, visible light intensity and audible noise level) and directly measured patient signals (electrocardiogram, electrooculogram, and body and limb posture) were designed and implemented. Results A novel alternative to the class III PSG system was demonstrated with independent boards capable of operating for more than 16 hours powered by a 750 mAh/3.7 V battery with 0.003% data loss during preliminary PSG exams. Additionally, a computer-based library capable of reading, decoding, estimating respiration through ECG, and calculating the heart rate was developed and described. Conclusion This article contributes to PSG research through the development of a new PSG system and the improvement of patient comfort. All software and hardware developed are fully open source and available on GitHub.

摘要 引言
睡眠质量受损会直接提升心脏病发作、肥胖及中风等多种疾病的发病风险，这使得多导睡眠监测（polysomnography, PSG）成为一项重要的公共卫生工具。然而，多导睡眠监测系统固有的缺陷给睡眠疾病的精准诊断带来了重重困难。作为II类多导睡眠监测系统的新型替代方案，本研究构建了一套包含三个模块的分布式系统，可同步监测环境变量与患者生理信号。该系统能够在部分场景下减轻患者接受多导睡眠监测检查时的不适感，免去患者在医疗或睡眠监测中心过夜监测的需求，同时支持自主搭建与基于互联网的诊断服务。

方法
本研究设计并实现了一套软硬件系统，可同步监测、处理环境参数（温度、湿度、可见光强度与可听噪声级）与直接采集的患者生理信号（心电图（electrocardiogram, ECG）、眼电图（electrooculogram, EOG）、躯体及肢体姿态），并将数据存储至微型SD（µSD）卡中。

结果
本研究验证了一款新型III类多导睡眠监测系统替代方案，其采用独立电路板设计，由750 mAh/3.7 V锂电池供电，可连续工作超过16小时，且在初步多导睡眠监测测试中数据丢失率仅为0.003%。此外，本研究开发并详述了一款基于计算机的软件库，可实现数据读取、解码，通过ECG估算呼吸频率，并计算心率。

结论
本研究通过开发新型多导睡眠监测系统并提升患者舒适度，为多导睡眠监测领域的研究提供了有益补充。本研究开发的全部软硬件均为完全开源项目，可在GitHub平台获取。