Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Sep 15, 2020
Date Accepted: Jan 5, 2021
Bed Sensor Technology for Objective Sleep Monitoring within the Clinical Rehabilitation Setting: a Feasibility Study
ABSTRACT
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 perspective for objective sleep analysis.
Objective:
The aim of the current 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 an one week period during their inhospital 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, and movement activity and bed exits) were reported.
Results:
In total, 24 participants (12 iSCI, 12 stroke) were measured. Five (3.8%) of the 130 nights had no 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-third of the missing HR and RR periods had a short duration of ≤120 s. Patients with an iSCI had an average nocturnal HR of 72 (13) beats per minute (bpm), RR of 16 (3) cycles per minute (cpm), and movement activity of 239 (116) activity points (AP), and had 86 reported and 84 recorded bed exits. Patients with a stroke had an average nocturnal HR of 61 (8) bpm, RR of 15 (1) cpm, and movement activity of 136 (49) AP, and had 42 reported and 57 recorded bed exits. Patients with an iSCI had significantly higher nocturnal HR (t(18)=-2.1, p=.042) and movement activity (t(18)=-1.2, p=.024) compared to stroke patients. Furthermore, there was a difference between self-reported and recorded bed exits per night in 15 of the 57 nights for iSCI patients and in 16 of the 42 nights for stroke patients.
Conclusions:
It is feasible to implement the bed sensor for continuous sleep monitoring in the clinical rehabilitation setting. The current study provides good foundation for further bed sensor development addressing sleep types and sleep disorders, to optimize care for rehabilitants.
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