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Sleep stage detection using a wristwatch-type physiological sensing device

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Abstract

Here, we propose an automated sleep stage classification method using a wristwatch-type physiological sensing device including a reflective photoelectric volume pulse sensor and a three-axis accelerometer to allow simple and inexpensive assessment of sleep quality. One hundred healthy volunteers (60 males and 40 females, aged 20–60 years old) wore the wristwatch-type physiological sensing device during overnight full polysomnography (PSG). Pulse-to-pulse intervals (PPI) and body movement indexes were determined from the records of the sensing device. The features extracted from the time-domain measures of PPI together with wrist movement indexes were utilized to develop an automated sleep stage classification system. The sleep stages detected by the proposed algorithm were compared with those determined by PSG utilizing the standard performance metrics (accuracy, recall, precision and F-measure). The mean rates of agreement with sleep stages on PSG categorized into two stages (wake and sleep), three stages (wake, non-REM, REM), and four stages (wake, light, and deep non-REM, REM) were 87.3, 74.3, and 68.5%, respectively. The accuracy of sleep stage detection indicated that the proposed method was sufficient for assessing sleep quality in healthy subjects without sleep disorders, and the wristwatch-type sensing device developed here can be used as a portable and easy-to-use home sleep monitoring device.

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Acknowledgements

The authors thank Toshiro Momose and the polysomnography technicians for their help and support. We would also like to thank the volunteers who participated in the sleep tests for their effort and enthusiastic cooperation throughout the study.

Funding

This study was supported by collaborative research expenses from Seiko Epson Corporation.

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Authors and Affiliations

  1. Department of Clinical Laboratory Sciences, Shinshu University School of Health Sciences, 3-1-1, Asahi, Matsumoto, 390-8621, Japan

    Keisaku Fujimoto

  2. Wearable Products Operations Divison, Seiko Epson Corporation, Shiojiri-machi, Shiojiri, Nagano, 390-0785, Japan

    Yimei Ding & Eizo Takahashi

Authors
  1. Keisaku Fujimoto
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  2. Yimei Ding
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  3. Eizo Takahashi
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Corresponding author

Correspondence to Keisaku Fujimoto.

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Conflict of interest

This study was supported by collaborative research expenses from Seiko Epson Corporation.

Ethical approval

This study was conducted in accordance with International Conference on Harmonization-Good Clinical Practice and the Declaration of Helsinki (2008), and was approved by the Institutional Research Ethics Committee of Shinshu University School of Medicine (no. 2321, no. 2755) and the Human Ethics Committee of Seiko Epson Corporation (no. AHR-2013-005, no. AHR-2014-006).

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All subjects were given an adequate explanation of the study and each provided written informed consent.

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Fujimoto, K., Ding, Y. & Takahashi, E. Sleep stage detection using a wristwatch-type physiological sensing device. Sleep Biol. Rhythms 16, 449–456 (2018). https://doi.org/10.1007/s41105-018-0175-5

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