Unobtrusive Sleep Health Assessment Using Impulse Radar: A Pilot Study in Older People.

IF 4.4 2区 医学 Q2 ENGINEERING, BIOMEDICAL
Maowen Yin, Charalambos Hadjipanayi, Kiran K G Ravindran, Alan Bannon, Adrien Rapeaux, Ciro Della Monica, Tor Sverre Lande, Derk-Jan Dijk, Timothy Constandinou
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Abstract

Objective: Ultra-wideband (UWB) radar technology has emerged as a promising alternative for creating portable and cost-effective in-home monitoring devices. Although there exists good evidence supporting its effectiveness in sleep monitoring, previous studies predominantly focus on younger, healthy participants. This research evaluates the applicability of commercial impulse UWB radar for sleep monitoring in older people and people with neurodegenerative disorders (NDDs).

Methods: 47 older people (mean age: 71.2 6.5, 18 with prodromal or mild Alzheimer's disease) participated in our overnight sleep trial with polysomnography (PSG) and UWB radar monitoring. Data processing based on multivariate empirical mode decomposition (MEMD) was employed to reconstruct cardiopulmonary activity and limb movements from radar signals. 29 features were extracted from the radar signals, and sleep stages were classified using a sequence-to-sequence neural network. Additionally, a cross-entropy-based approach was used to quantify uncertainties in the radar classification model and provide confidence in the classification.

Results: The UWB radar system demonstrated high accuracy in detecting body movements, reconstructing respiratory patterns, and monitoring heart rate. For sleep stage classification, the results showed a Kappa coefficient of 0.63 and an average accuracy of 74.4% across wake, REM sleep, light sleep (N1 + N2), and deep sleep (N3) categories.

Conclusion: The proposed method reliably monitors physiological changes during sleep, which suggests its potential as a cost-effective alternative to traditional sleep monitoring devices.

Significance: The findings underscore the viability of UWB radar as a nonintrusive, forward-looking sleep assessment tool that could significantly benefit care for older people and people with neurodegenerative disorders.

使用脉冲雷达进行睡眠健康评估:一项针对老年人的初步研究。
目的:超宽带 (UWB) 雷达技术已成为制造便携式、经济型家用监测设备的理想选择。虽然有充分的证据支持其在睡眠监测方面的有效性,但以前的研究主要集中在年轻、健康的参与者身上。方法:47 位老年人(平均年龄:71.2 6.5 岁,18 位患有前驱或轻度阿尔茨海默病)参加了我们的夜间睡眠试验,并接受了多导睡眠图 (PSG) 和 UWB 雷达监测。我们采用基于多变量经验模式分解(MEMD)的数据处理方法,从雷达信号中重建心肺活动和肢体运动。从雷达信号中提取了 29 个特征,并使用序列到序列神经网络对睡眠阶段进行了分类。此外,还采用了一种基于交叉熵的方法来量化雷达分类模型中的不确定性,并为分类提供置信度:结果:UWB 雷达系统在检测身体运动、重建呼吸模式和监测心率方面都表现出很高的准确性。在睡眠阶段分类方面,结果显示 Kappa 系数为 0.63,在清醒、快速眼动睡眠、浅睡眠(N1 + N2)和深睡眠(N3)类别中的平均准确率为 74.4%:结论:所提出的方法能可靠地监测睡眠过程中的生理变化,这表明它有潜力成为传统睡眠监测设备的一种具有成本效益的替代品:研究结果强调了超宽带波雷达作为一种非侵入性、前瞻性睡眠评估工具的可行性,它将极大地改善对老年人和神经退行性疾病患者的护理。
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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来源期刊
IEEE Transactions on Biomedical Engineering
IEEE Transactions on Biomedical Engineering 工程技术-工程:生物医学
CiteScore
9.40
自引率
4.30%
发文量
880
审稿时长
2.5 months
期刊介绍: IEEE Transactions on Biomedical Engineering contains basic and applied papers dealing with biomedical engineering. Papers range from engineering development in methods and techniques with biomedical applications to experimental and clinical investigations with engineering contributions.
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