ArticleJMIR mHealth and uHealth2021
Bed Sensor Technology for Objective Sleep Monitoring Within the Clinical Rehabilitation Setting: Observational Feasibility Study.
Article in JMIR mHealth and uHealth, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.
- Evaluation of the Accuracy of Contactless Consumer Sleep-Tracking Devices Application in Human Experiment: A Systematic Review and Meta-Analysis.Sensors (Basel, Switzerland) · 2023Pooled it
- Evaluating the Feasibility of Low-Cost, Contactless Consumer Sleep-Tracking Devices as Measurement Tools for Preliminary Sleep Research.Sensors (Basel, Switzerland) · 2026Article
- Digital Technology for Sleep Symptoms in Parkinson's Disease: A Scoping Review.Journal of movement disorders · 2026Article
- Continuous At-Home Monitoring of Nighttime Bed Behavior in Frontotemporal Dementia.Neurology open access · 2026Article
- Exploring bed sensor technology: interdisciplinary insights in a geriatric assessment inpatient setting.The Gerontologist · 2026Article
- Multimodal Sleep Measurement and Alignment Analysis in Outpatients With Major Depressive Episode: Observational Study.JMIR mHealth and uHealth · 2025Observational
- Unobtrusive Bed Monitor State of the Art.Sensors (Basel, Switzerland) · 2025Review
- Comparing actigraphy and diary to measure daily and average sleep in firefighters: a Bland-Altman analysis.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2024Article
- Changepoint Detection in Heart Rate Variability Indices in Older Patients Without Cancer at End of Life Using Ballistocardiography Signals: Preliminary Retrospective Study.JMIR formative research · 2024Article
- Article
- Device-based and subjective measurements of sleep in children with cerebral palsy: a comparison of sleep diary, actigraphy, and bed sensor data.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2023Article
- Detection and Monitoring of Viral Infections via Wearable Devices and Biometric Data.Annual review of biomedical engineering · 2022Review
- Sleep monitoring challenges in patients with neurocognitive disorders: A cross-sectional analysis of missing data from activity trackers.Health science reports · 2022Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSince 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.
objectiveThe aim of this study was to investigate the feasibility of a bed sensor for continuous sleep monitoring overnight in a clinical rehabilitation center.
methodsPatients 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.
resultsIn 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
conclusionsIt 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.
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