Unsupervised Artefact Detection and Screening Using Emfit Sensor in Patients With Sleep Apnea

Dorien Huysmans, B. Buyse, D. Testelmans, S. Huffel, C. Varon
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引用次数: 1

Abstract

Sleep apnea is one of the most common sleep disorders. As sleep apnea is associated to adverse health outcomes, early screening is promoted through unobtrusive, cheap and simple systems for sleep monitoring. A commercial pressure sensor meeting these requirements is the Emfit QS, which was integrated in a bed of a specialized sleep center. The sensor is pressure based and highly sensitive to movement. This causes artefacts of different morphologies in the signal. An unsupervised artefact detection method was developed to avoid burdensome manual labelling of artefacts in the signal and enabling further analysis. Moreover, the percentage of detected artefacts was useful for assessment of the sleep apnea severity as movements partially originate from apneic arousals. Severe sleep apnea patients could be identified with a sensitivity of 80% and a specificity of 87%. The proposed approach offers an ambivalent tool for artefact detection and unobtrusive screening of sleep apnea patients at home.
Emfit传感器在睡眠呼吸暂停患者中的无监督伪影检测和筛选
睡眠呼吸暂停是最常见的睡眠障碍之一。由于睡眠呼吸暂停与不良健康结果有关,因此通过不显眼、廉价和简单的睡眠监测系统促进早期筛查。满足这些要求的商业压力传感器是Emfit QS,它集成在一个专门的睡眠中心的床上。该传感器基于压力,对运动高度敏感。这导致了信号中不同形态的伪影。开发了一种无监督伪影检测方法,以避免对信号中的伪影进行繁琐的人工标记并进行进一步分析。此外,检测到的伪象百分比对于评估睡眠呼吸暂停严重程度是有用的,因为运动部分源于呼吸暂停唤醒。重度睡眠呼吸暂停患者的识别灵敏度为80%,特异性为87%。提出的方法提供了一个矛盾的工具,人工检测和不显眼的筛选睡眠呼吸暂停患者在家里。
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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