Summary
International Symposium on Nonlinear Theory and its Applications
2017
Session Number:A1L-C
Session:
Number:A1L-C-2
Evaluation of Sleep Quality Based on Environment and Vital Sensor Signals Using Big Data Analysis and Deep Learning
Minami Tsuchiya, Atsushi Tanaka, Muneki Yasuda, Tomochika Harada, Michio Yokoyama,
pp.38-41
Publication Date:2017/12/4
Online ISSN:2188-5079
Summary:
Big data analysis and deep learning are used to investigate factors which influence the subjective satisfaction of sleep. Environmental and vital signs data are obtained throughout the experiment by a sensing bed system. Relationships between over 300,000 measured data points are visualized and analyzed. Deep learning indicates that temperature difference between the inside and the outside of the bed contributes to subjective satisfaction of sleep during the warm and cold period. Furthermore it is shown that respiratory frequency has an influence on sleep satisfaction through deep learning analysis.