Contactless remote monitoring of sleep: evaluating the feasibility of an under-mattress sensor mat in a real-life deployment

Ibrahim Sadek and Bessam Abdulrazak

Health Systems, 2023, vol. 12, issue 3, 264-280

Abstract: Sleep is so important, particularly for the elderly. The lack of sleep may increase the risk of cognitive decline. Similarly, it may also increase the risk of Alzheimer’s disease. Nonetheless, many people underestimate the importance of getting enough rest and sleep. In-laboratory polysomnography is the gold-standard method for assessing the quality of sleep. This method is considered impractical in the clinical environment, seen as labour-intensive and expensive owing to its specialised equipment, leading to long waiting lists. Hence, user-friendly (remote and non-intrusive) devices are being developed to help patients monitor their sleep at home. In this paper, we first discuss commercially-available non-wearable devices that measure sleep, in which we highlight the features associated with each device, including sensor type, interface, outputs, dimensions, power supply, and connectivity. Second, we evaluate the feasibility of a non-wearable device in a free-living environment. The deployed device comprises a sensor mat with an integrated micro-bending multimode fibre. Raw sensor data were gathered from five senior participants living in a senior activity centre over a few to several weeks. We were able to analyse the participants’ sleep quality using various sleep parameters deduced from the sensor mat. These parameters include the wake-up time, bedtime, the time in bed, nap time. Vital signs, namely heart rate, respiratory rate, and body movements, were also reported to detect abnormal sleep patterns. We have employed pre-and post-surveys reporting each volunteer’s sleep hygiene to confirm the proposed system’s outcomes for detecting the various sleep parameters. The results of the system were strongly correlated with the surveys for reporting each sleep parameter. Furthermore, the system proved to be highly effective in detecting irregular patterns that occurred during sleep.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/20476965.2022.2072777 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:thssxx:v:12:y:2023:i:3:p:264-280

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/thss20

DOI: 10.1080/20476965.2022.2072777

Access Statistics for this article

Health Systems is currently edited by Sally Brailsford

More articles in Health Systems from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().