Long-Term Sleep Assessment by Unobtrusive Pressure Sensor Arrays

S. S. Gilakjani, M. Bouchard, R. Goubran, F. Knoefel
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引用次数: 8

Abstract

Due to a globally aging population, there is a growing demand for smart home technology which can serve to monitor the health and safety of older adults. Sleep monitoring has emerged as a crucial element of this monitoring. While polysomnography (PSG) is an effective and accurate tool for sleep monitoring, it is obtrusive as the user must wear the instruments during the experiment. Therefore, there has been a growing interest in deploying unobtrusive sleep monitoring devices, specifically for long-term patient monitoring. This paper performs a comprehensive investigation on long-term sleep pattern changes by investigating bed occupancy, number of bed exits during day and breathing rate variability. Measurements were made using unobtrusive pressure sensitive sensor arrays on data captured from several participants collected in a long-term basis, which provided a large volume of data. Multiple algorithms are proposed that can be described as movement detection, sensor data fusion and bed occupancy detection. The methods developed in the paper and the related findings can be of interest for future clinical remote patient monitoring systems.
不显眼的压力传感器阵列长期睡眠评估
由于全球人口老龄化,对智能家居技术的需求不断增长,智能家居技术可以监测老年人的健康和安全。睡眠监测已经成为这种监测的一个关键因素。虽然多导睡眠图(PSG)是一种有效而准确的睡眠监测工具,但由于用户在实验过程中必须佩戴仪器,因此它具有突兀性。因此,人们对部署不显眼的睡眠监测设备越来越感兴趣,特别是用于长期患者监测。本文通过调查床位占用率、白天床位数和呼吸频率变异性,对长期睡眠模式的变化进行了全面的调查。测量是使用不显眼的压力敏感传感器阵列对从几个参与者长期收集的数据进行的,这些数据提供了大量的数据。提出了运动检测、传感器数据融合和床位占用检测等算法。本文开发的方法和相关发现可以对未来的临床远程患者监测系统感兴趣。
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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