临床康复环境中客观睡眠监测的床传感器技术：观察性可行性研究。
Bed Sensor Technology for Objective Sleep Monitoring Within the Clinical Rehabilitation Setting: Observational Feasibility Study.
机构信息
Department of Research, Sint Maartenskliniek, Nijmegen, Netherlands.
Department of Rehabilitation, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands.
出版信息
JMIR Mhealth Uhealth. 2021 Feb 8;9(2):e24339. doi: 10.2196/24339.
BACKGROUND
Since adequate sleep is essential for optimal inpatient rehabilitation, there is an increased interest in sleep assessment. Unobtrusive, contactless, portable bed sensors show great potential for objective sleep analysis.
OBJECTIVE
The aim of this study was to investigate the feasibility of a bed sensor for continuous sleep monitoring overnight in a clinical rehabilitation center.
METHODS
Patients with incomplete spinal cord injury (iSCI) or stroke were monitored overnight for a 1-week period during their in-hospital rehabilitation using the Emfit QS bed sensor. Feasibility was examined based on missing measurement nights, coverage percentages, and missing periods of heart rate (HR) and respiratory rate (RR). Furthermore, descriptive data of sleep-related parameters (nocturnal HR, RR, movement activity, and bed exits) were reported.
RESULTS
In total, 24 participants (12 iSCI, 12 stroke) were measured. Of the 132 nights, 5 (3.8%) missed sensor data due to Wi-Fi (2), slipping away (1), or unknown (2) errors. Coverage percentages of HR and RR were 97% and 93% for iSCI and 99% and 97% for stroke participants. Two-thirds of the missing HR and RR periods had a short duration of ≤120 seconds. Patients with an iSCI had an average nocturnal HR of 72 (SD 13) beats per minute (bpm), RR of 16 (SD 3) cycles per minute (cpm), and movement activity of 239 (SD 116) activity points, and had 86 reported and 84 recorded bed exits. Patients with a stroke had an average nocturnal HR of 61 (SD 8) bpm, RR of 15 (SD 1) cpm, and movement activity of 136 (SD 49) activity points, and 42 reported and 57 recorded bed exits. Patients with an iSCI had significantly higher nocturnal HR (t=-2.1, P=.04) and movement activity (t=-1.2, P=.02) compared to stroke patients. Furthermore, there was a difference between self-reported and recorded bed exits per night in 26% and 38% of the nights for iSCI and stroke patients, respectively.
CONCLUSIONS
It is feasible to implement the bed sensor for continuous sleep monitoring in the clinical rehabilitation setting. This study provides a good foundation for further bed sensor development addressing sleep types and sleep disorders to optimize care for rehabilitants.
背景
充足的睡眠对最佳住院康复至关重要，因此人们对睡眠评估的兴趣日益增加。非接触式、便携式床传感器在客观的睡眠分析方面具有很大的潜力。
目的
本研究旨在调查在临床康复中心使用床传感器进行连续夜间睡眠监测的可行性。
方法
使用 Emfit QS 床传感器，对不完全性脊髓损伤（iSCI）或脑卒中患者进行 1 周的夜间连续监测。根据缺失的测量夜数、覆盖百分比以及缺失的心率（HR）和呼吸率（RR）时间段来评估可行性。此外，还报告了与睡眠相关的参数（夜间 HR、RR、活动和离床）的描述性数据。
结果
共测量了 24 名参与者（12 名 iSCI，12 名脑卒中）。在 132 个夜晚中，有 5 个（3.8%）因 Wi-Fi（2 个）、滑落（1 个）或未知（2 个）错误而丢失了传感器数据。iSCI 参与者的 HR 和 RR 的覆盖百分比分别为 97%和 93%，脑卒中参与者分别为 99%和 97%。三分之二的缺失 HR 和 RR 时间段持续时间较短，≤120 秒。iSCI 患者的平均夜间 HR 为 72（SD 13）次/分钟，RR 为 16（SD 3）次/分钟，活动量为 239（SD 116）个活动点，报告的离床次数为 86 次，记录的离床次数为 84 次。脑卒中患者的平均夜间 HR 为 61（SD 8）次/分钟，RR 为 15（SD 1）次/分钟，活动量为 136（SD 49）个活动点，报告的离床次数为 42 次，记录的离床次数为 57 次。与脑卒中患者相比，iSCI 患者的夜间 HR（t=-2.1，P=.04）和活动量（t=-1.2，P=.02）明显更高。此外，iSCI 和脑卒中患者在 26%和 38%的夜晚中，自我报告的离床次数和记录的离床次数存在差异。
结论
在临床康复环境中实施连续睡眠监测的床传感器是可行的。本研究为进一步开发针对睡眠类型和睡眠障碍的床传感器提供了良好的基础，以优化康复者的护理。
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