Nonlinear Theory and Its Applications, IEICE
Online ISSN : 2185-4106
ISSN-L : 2185-4106
Special Issue on Recent Progress in Nonlinear Theory and Its Applications
Estimation of sleep onset and awaking time using a deep neural network with physiological data during sleep
Minami TsuchiyaAtsushi TanakaMuneki YasudaTomochika HaradaSeung-Il ChoMichio Yokoyama
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2019 Volume 10 Issue 4 Pages 366-372


A deep Neural Network (DNN) is used to estimate the sleep onset and awaking time of a subject with physiological data during sleep, in order to control the sleeping environment based on sleep phase. The results of the estimation from 40 minutes before the actual sleeping time show approximately 2.8 minutes mean error. Regarding awaking time, the results of the estimation from 120 minutes before show approximately 9.9 minutes mean error. Furthermore, the results of estimation in case of the range from 60 to 20 minutes before the actual awakening time show approximately 7.5 minutes mean error. The proposed DNN estimation is found to be effective for control of a comfortable awaking environment.

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© 2019 The Institute of Electronics, Information and Communication Engineers
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