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Open AccessArticle

Sleep Stage Classification by a Combination of Actigraphic and Heart Rate Signals

1
Graduate School of Medical Sciences, Nagoya City University, Nagoya 467-8602, Japan
2
Sleep Disorder Center, Aichi Medical University Hospital, Nagakute 480-1195, Japan
3
Gifu Mates Sleep Clinic, Gifu 500-8384, Japan
*
Author to whom correspondence should be addressed.
J. Low Power Electron. Appl. 2017, 7(4), 28; https://doi.org/10.3390/jlpea7040028
Received: 25 September 2017 / Revised: 9 November 2017 / Accepted: 9 November 2017 / Published: 13 November 2017
(This article belongs to the Special Issue Low-Power Electronic Circuits for Monolithic Smart Wireless Sensors)
Although heart rate variability and actigraphic data have been used for sleep-wake or sleep stage classifications, there are few studies on the combined use of them. Recent wearable sensors, however, equip both pulse wave and actigraphic sensors. This paper presents results on the performance of sleep stage classification by a combination of heart rate and actigraphic signals. We studied 40,643 epochs (length 3 min) of polysomnographic data in 289 subjects. A combined model, consisting of autonomic functional indices from heart rate variability and body movement indices derived from actigraphic data, discriminated non-rapid-eye-movement (REM) sleep from waking/REM sleep with 76.9% sensitivity, 74.5% specificity, 75.8% accuracy, and a Cohen’s kappa of 0.514. The combination was also useful for discriminating between REM sleep and waking at 77.2% sensitivity, 72.3% specificity, 74.5% accuracy, and a kappa of 0.491. View Full-Text
Keywords: actigraphy; heart rate variability; polysomnography; sleep; sleep stage actigraphy; heart rate variability; polysomnography; sleep; sleep stage
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MDPI and ACS Style

Yuda, E.; Yoshida, Y.; Sasanabe, R.; Tanaka, H.; Shiomi, T.; Hayano, J. Sleep Stage Classification by a Combination of Actigraphic and Heart Rate Signals. J. Low Power Electron. Appl. 2017, 7, 28.

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