Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
Novelda AS, Trondheim, Norway.
J Sleep Res. 2022 Dec;31(6):e13687. doi: 10.1111/jsr.13687. Epub 2022 Jul 6.
This work aimed to evaluate if a contact-free radar sensor can be used to observe ultradian patterns in sleep physiology, by way of a data processing tool known as Locomotor Inactivity During Sleep (LIDS). LIDS was designed as a simple transformation of actigraphy recordings of wrist movement, meant to emphasise and enhance the contrast between movement and non-movement and to reveal patterns of low residual activity during sleep that correlate with ultradian REM/NREM cycles. We adapted the LIDS transformation for a radar that detects body movements without direct contact with the subject and applied it to a dataset of simultaneous recordings with polysomnography, actigraphy, and radar from healthy young adults (n = 12, four nights of polysomnography per participant). Radar and actigraphy-derived LIDS signals were highly correlated with each other (r > 0.84), and the LIDS signals were highly correlated with reduced-resolution polysomnographic hypnograms (r >0.80, r >0.76). Single-harmonic cosine models were fitted to LIDS signals and hypnograms; significant differences were not found between their amplitude, period, and phase parameters. Mixed model analysis revealed similar slopes of decline per cycle for radar-LIDS, actigraphy-LIDS, and hypnograms. Our results indicate that the LIDS technique can be adapted to work with contact-free radar measurements of body movement; it may also be generalisable to data from other body movement sensors. This novel metric could aid in improving sleep monitoring in clinical and real-life settings, by providing a simple and transparent way to study ultradian dynamics of sleep using nothing more than easily obtainable movement data.
本研究旨在评估非接触式雷达传感器是否可用于通过一种称为睡眠期间活动不足 (LIDS) 的数据处理工具来观察睡眠生理学中的超慢波模式。LIDS 是一种对腕部运动活动记录仪的简单转换，旨在强调和增强运动与非运动之间的对比度，并揭示与超慢波 REM/NREM 周期相关的睡眠期间低残留活动模式。我们将 LIDS 转换适用于一种无需与受试者直接接触即可检测身体运动的雷达，并将其应用于来自健康年轻成年人的同时多导睡眠图、活动记录仪和雷达记录的数据集（n=12，每位参与者有四晚多导睡眠图记录）。雷达和活动记录仪衍生的 LIDS 信号彼此高度相关（r>0.84），并且 LIDS 信号与低分辨率多导睡眠图催眠图高度相关（r>0.80，r>0.76）。对 LIDS 信号和催眠图拟合单谐波余弦模型；它们的振幅、周期和相位参数之间没有发现显著差异。混合模型分析显示，雷达-LIDS、活动记录仪-LIDS 和催眠图的每个周期的下降斜率相似。我们的研究结果表明，LIDS 技术可以适应使用非接触式雷达测量身体运动；它也可能适用于来自其他身体运动传感器的数据。这种新的指标可以通过提供一种简单透明的方法来研究睡眠的超慢波动力学，从而有助于改善临床和现实生活中的睡眠监测，而无需使用其他更容易获得的运动数据。
