Journal
JOURNAL OF CLINICAL SLEEP MEDICINE
Volume 13, Issue 11, Pages 1301-1310Publisher
AMER ACAD SLEEP MEDICINE
DOI: 10.5664/jcsm.6802
Keywords
chest sensor; polysomnography; sleep; validation; wearable sensor
Categories
Funding
- National Institute of health (NIH), National Cancer Institute [1R21CA190933-01A1]
- University of Arizona (UA)
- Baylor College of Medicine (BCM)
Ask authors/readers for more resources
Study Objectives: To improve sleep quality assessment using a single chest-worn sensor by extracting body acceleration and sleep position changes. Methods: Sleep patterns of 21 participants (50.8 +/- 12.8 years, 47.8% female) with self-reported sleep problems were simultaneously recorded using a chest sensor (Chest), an Actiwatch (Wrist), and polysomnography (PSG) during overnight sleep laboratory assessment. An algorithm for Chest was developed to detect sleep/wake epochs based on body acceleration and sleep position/postural changes data, which were then used to estimate sleep parameters of interest. Comparisons between Chest and Wrist with respect to PSG were performed. Identification of sleep/wake epochs was assessed by estimating sensitivity, specificity, and accuracy. Agreement between sensor-derived sleep parameters and PSG was assessed using correlation coefficients and Bland-Altman analysis. Results: Chest identified sleep/wake epochs with an accuracy of on average 6% higher than Wrist (85.8% versus 79.8%). Similar trends were observed for sensitivity/specificity values. Correlation between Wrist and PSG was poor for most of the sleep parameters of interest (r = 0.0-0.3); however, Chest and PSG correlation showed moderate to strong agreement (r = 0.4-0.8) with relatively low bias and high precision bias (precision): 9.2 (13.2) minutes for sleep onset latency; 17.3(34.8) minutes for total sleep time; 7.5 (29.8) minutes for wake after sleep onset; and 2.0 (7.3)% for sleep efficacy. Conclusions: Combination of sleep postural/position changes and body acceleration improved detection of sleep/wake epochs compared to wrist acceleration alone. The chest sensors also improved estimation of sleep parameters of interest with stronger agreement with PSG. Our findings may expand the application of wearable sensors to clinically assess sleep outside of a sleep laboratory.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available