Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Dec 12, 2020
Date Accepted: Apr 12, 2021
Sleep detection for younger adults, healthy older adults, and older adults living with dementia using wrist-worn temperature and actigraphy: Prototype Testing and Case Study Analysis
ABSTRACT
Background:
Sleep is essential to one’s health and quality of life. Wearable technologies that use motion and temperature sensors have made it possible to self-monitor sleep. While there is a growing body of research on sleep monitoring using wearables for healthy young-to-middle-aged adults, few studies have focused on older adults, including those living with dementia.
Objective:
This research investigated how age and dementia can impact sleep detection by movement and wrist temperature.
Methods:
10 younger adults, 10 healthy older adults, and 8 older adults living with dementia (OAWD) were recruited. Each participant wore a Mi Band 2 (accemetry-based sleep detection) and our custom-built wristband (actigraphy and wrist temperature) 24-hours a day for two weeks and was asked to keep a daily sleep journal. Sleep parameters detected by the Mi Band 2 were compared with sleep journals and visual analysis of actigraphy and temperature data was performed.
Results:
The absolute difference of sleep onset and offset between the sleep journals and Mi Band 2 were: 0:39 ± 0:51 min and 0:31 ± 0:52 min for younger adults, 0:49 ± 0:58 min and 0:33 ± 0:58 min for older adults, and 4:13 ± 1:14 and 2:41 ± 1:06 for OAWD. The Mi Band 2 was unable to accurately detect sleep for three healthy older adults and all of the OAWD. The average Sleep/Wake temperature difference (SWTD) of OAWD (1.26 ± 0.76 ℃) was significantly lower than that of healthy older adults (2.04 ± 0.66 ℃) and healthy younger adults (2.48 ± 0.83 ℃). Actigraphy data showed that older adults had more movement during sleep compared to younger adults and that this trend appears to increase for those with dementia.
Conclusions:
The Mi Band 2 did not accurately detect sleep for older adults who had greater levels of night time movement. As more nighttime movement appears to be a phenomenon that increases in prevalence with age and even more so with dementia, further research needs to be done with a larger sample size and greater diversity of commercially available wearables to explore these trends more conclusively. All participants, including older adults and OAWD, had a distinct day/night (sleep/awake) wrist temperature contrast, which suggests this feature could be leveraged to create more robust and broadly applicable sleep detection algorithms.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.