Sensory system for the sleep disorders detection in the geriatric population

M. Alberto, M. Ruano, Miguel A. Herrero Ramiro, A. Jiménez, J. J. García, E. Díaz
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引用次数: 5

Abstract

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.
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老年人睡眠障碍检测的感觉系统
本文介绍了一种用于老年门诊患者睡眠障碍检测的遥感系统。虽然最准确的解决方案是在睡眠诊所进行深入研究,但这对老年人来说并不是一个现实的环境。目的是让病人呆在家里,不改变他们的日常生活,临床医生得到客观的信息,以便对睡眠障碍做出正确的诊断。作为实现家庭远程监测系统的第一步,本工作引入了一个身体传感器网络(BSN)来监测各种生命信号,如心电图(ECG)和肌电图(EMG),以收集足够的信息用于睡眠障碍诊断,重点是检测阻塞性睡眠呼吸暂停。本研究提出了一种基于单导联心电图信号的功率谱分析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,灵敏度约为85%。
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