Learning Multiple Band-Pass Filters for Sleep Stage Estimation: Towards Care Support for Aged Persons

Keiki TAKADAMA  Kazuyuki HIROSE  Hiroyasu MATSUSHIMA  Kiyohiko HATTORI  Nobuo NAKAJIMA  

IEICE TRANSACTIONS on Communications   Vol.E93-B   No.4   pp.811-818
Publication Date: 2010/04/01
Online ISSN: 1745-1345
DOI: 10.1587/transcom.E93.B.811
Print ISSN: 0916-8516
Type of Manuscript: Special Section PAPER (Special Section on Information and Communication Technology for Wellness and Medical Applications)
sleep stage estimation,  learning classifier system,  care support,  heartbeat,  

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This paper proposes the sleep stage estimation method that can provide an accurate estimation for each person without connecting any devices to human's body. In particular, our method learns the appropriate multiple band-pass filters to extract the specific wave pattern of heartbeat, which is required to estimate the sleep stage. For an accurate estimation, this paper employs Learning Classifier System (LCS) as the data-mining techniques and extends it to estimate the sleep stage. Extensive experiments on five subjects in mixed health confirm the following implications: (1) the proposed method can provide more accurate sleep stage estimation than the conventional method, and (2) the sleep stage estimation calculated by the proposed method is robust regardless of the physical condition of the subject.