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Sensory system for the sleep disorders detection in the geriatric population

机译:睡眠障碍检测的感官系统在老年群体中检测

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This paper introduces the proposal of a remote sensory system for the detection of sleep disorders in geriatric outpatients. Although the most accurate solution would be an in-depth study in a sleep clinic, it is not a realistic environment for the elderly. The objective is that the patient stays at home, and without changing their daily routines, the clinicians get objective information in order to make a correct diagnosis of the sleep disorders. As a first step towards achieving a home remote monitory system, this work introduces a Body Sensor Network (BSN) to monitor various vital signals as Electrocardiogram (ECG) and Electromyogram (EMG) in order to collect enough information for sleep disorder diagnosis, focusing on the detection of obstructive sleep apnea. This work proposes an algorithm to infer obstructive sleep apnea (OSA) based on power spectral analysis of ECG signals from a single-lead electrocardiogram, demonstrating the feasibility of BSN to detect OSA with around 85% sensitivity.
机译:本文介绍了远程感官系统的提议,用于检测老年门诊患者的睡眠障碍。虽然最准确的解决方案是睡眠诊所的深入研究,但它不是老年人的现实环境。目的是,患者在家里留下,而不会改变他们的日常生活,临床医生获得客观信息,以便对睡眠障碍进行正确的诊断。作为实现家庭远程监管系统的第一步,这项工作引入了一个身体传感器网络(BSN),以监测各种重要信号作为心电图(ECG)和电拍照(EMG),以便收集足够的信息,以便睡眠障碍诊断,专注于检测阻塞性睡眠呼吸暂停。这项工作提出了一种基于来自单引灯心电图的ECG信号的功率谱分析来推断阻塞性睡眠呼吸暂停(OSA)的算法,证明了BSN检测OSA的可行性,其灵敏度约为85℃。

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