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Article type: Research Article
Authors: Walsh, Lorcan; | McLoone, Seán
Affiliations: CASALA, Dundalk Institute of Technology, Louth, Ireland | School of Electronics, Electrical Engineering and Computer Science, Queens University Belfast, Northern Ireland, UK
Note: [] Corresponding author. E-mail: [email protected].
Abstract: Sleep quality and duration are increasingly recognised as being important prognostic parameters in the assessment of an individual's health. However, reliable non-invasive long-term monitoring of sleep in a non-clinical setting remains a challenging problem. This paper describes the validation of a novel under mattress pressure sensing sleep monitoring modality that can be seamlessly integrated into existing home environments and provides a pervasive and distributed solution for monitoring long-term changes in sleep patterns and sleep disorders in adults. 410 minutes of concomitant Under Mattress Bed Sensor (UMBS) and strain gauge data were analysed from eight healthy adults lying passively. In this analysis, customised respirations rate detection algorithms yielded a mean difference of −0.12 breaths per five minutes and a mean percentage error (MPE) of 0.16% when the sensor was placed beneath the mattress. 1,491 minutes of UMBS and video data were recorded simultaneously from four participants in order to assess the movement detection efficacy of customised UMBS algorithms. These algorithms yielded accuracies, sensitivities and specificities of over 90% when compared to a video-based movement detection gold standard. A reduced data set (267 minutes) of wrist actigraphy, the gold standard ambulatory sleep monitor, was recorded. The UMBS was shown to outperform the movement detection ability of wrist actigraphy and has the added advantage of not requiring active subject participation.
Keywords: Unobtrusive, sleep, sleep monitoring, older adults, e-Health
DOI: 10.3233/AIS-140264
Journal: Journal of Ambient Intelligence and Smart Environments, vol. 6, no. 4, pp. 385-401, 2014
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