Sleep Stage Evaluation System Based on Multi-Channel Sensors Using Kernel SVM 


Vol. 46,  No. 1, pp. 154-161, Jan.  2021
10.7840/kics.2021.46.1.154


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  Abstract

In this paper, we propose a sleep state evaluation system based on multi-channel sensor for monitoring of sleep conditions. Polysomnography is generally adopted as a method for sleep state evaluation. However, it degrades sleep quality due to environmental change. Besides, the cost is high for the public to afford. Moreover, single-channel sensor used in previous researches has less accuracy in sleep stage classification. The proposed system uses wireless wearable sensors to classify and evaluate sleep. It classifies sleep in to three stages, WAKE/NREM/REM by analyzing bio data such as electrocardiogram, movement, respiration and heart rate. The classified results are used to calculate sleep efficiency which provides convenience in life to the user.

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  Cite this article

[IEEE Style]

J. Kang, S. Cho, H. Oh, "Sleep Stage Evaluation System Based on Multi-Channel Sensors Using Kernel SVM," The Journal of Korean Institute of Communications and Information Sciences, vol. 46, no. 1, pp. 154-161, 2021. DOI: 10.7840/kics.2021.46.1.154.

[ACM Style]

Ji-yeon Kang, Sung-yoon Cho, and Hyun-woo Oh. 2021. Sleep Stage Evaluation System Based on Multi-Channel Sensors Using Kernel SVM. The Journal of Korean Institute of Communications and Information Sciences, 46, 1, (2021), 154-161. DOI: 10.7840/kics.2021.46.1.154.

[KICS Style]

Ji-yeon Kang, Sung-yoon Cho, Hyun-woo Oh, "Sleep Stage Evaluation System Based on Multi-Channel Sensors Using Kernel SVM," The Journal of Korean Institute of Communications and Information Sciences, vol. 46, no. 1, pp. 154-161, 1. 2021. (https://doi.org/10.7840/kics.2021.46.1.154)