Department of Family Medicine, Inje University Ilsan Paik Hospital, Juhwa-ro, Ilsanseo-gu, Goyang-Si, Gyeonggi-Do, Korea.
Department of Neurology, Dongguk University Ilsan Hospital, Dongguk-ro, Goyang-si, Ilsandong-gu, Gyeonggi-do, Korea.
Technol Health Care. 2020;28(4):439-446. doi: 10.3233/THC-192036.
Sleep monitoring is essential to maintain a healthy life, especially for the elderly who want to age well. Among various forms of sleep devices, the non-wearable and home-adapted device might be preferred because it can be easily used.
In this study, we evaluated the performance of a non-contact home-adapted device compared to polysomnography (PSG), a gold standard method.
As a preliminary study, eight subjects were recorded over fourteen nights through PSG. The non-contact home-adapted device comprised a microwave sensor, passive infrared sensor, and smartphone application. Through the device, heart rate, respiratory rate, and body movement were collected and used to estimate sleep stages. Sleep structure was labeled in four classes: wake, REM, light, and deep sleep, and were classified using a weighted k-nearest neighbor algorithm.
The device correctly estimated sleep structures with an overall epoch-by-epoch accuracy of 98.65% ± 0.05% based on leave-one-out cross-validation. The device showed significantly positive correlations with PSG in sleep indices including total sleep time, sleep efficiency, and wake after sleep onset.
Our findings demonstrate a good performance of this non-contact and home-adapted device and suggest its suitability for sleep monitoring.
睡眠监测对于维持健康的生活至关重要,特别是对于希望健康长寿的老年人而言。在各种形式的睡眠设备中,非穿戴式且适合家庭使用的设备可能更受欢迎,因为它易于使用。
本研究旨在评估一种非接触式家庭适应设备与金标准多导睡眠图(PSG)相比的性能。
作为初步研究,8 名受试者通过 PSG 记录了 14 个晚上的数据。非接触式家庭适应设备由微波传感器、被动红外传感器和智能手机应用程序组成。通过该设备,收集心率、呼吸率和身体运动等数据,并用于估计睡眠阶段。睡眠结构被标记为四个等级:清醒、REM、浅睡和深睡,并使用加权 K 最近邻算法进行分类。
基于留一法交叉验证,该设备在睡眠结构的逐epoch 准确性方面达到了 98.65%±0.05%的总体准确率。该设备在总睡眠时间、睡眠效率和睡眠后觉醒时间等睡眠指标上与 PSG 显示出显著的正相关关系。
我们的研究结果表明,这种非接触式和家庭适应的设备具有良好的性能,表明其适用于睡眠监测。