Improving sleep stage estimation accuracy by circadian rhythm extracted from a low frequency component of heart rate

Akari Tobaru, Fumito Uwano, Takuya Iwase, Kazuma Matsumoto, Ryo Takano, Yusuke Tajima, Yuta Umenai, Keiki Takadama

Research output: Contribution to conferencePaperpeer-review

1 Citation (Scopus)

Abstract

This paper described that proposing a novel method to estimate the sleep stage by biological data obtained with a non-contact sensor devices and that investigating its effectiveness. Proposed method focused on circadian rhythm to consider of a day biological rhythm in overall sleeping in addition to employ the Haradas method. To verify the effectiveness of the proposed method, we derived the subject experiment that compared with the evaluation accuracy by the previous method with adjustment of circadian rhythm. As the experimental results, the following implications have been revealed: (1) the accuracy of the sleep stage estimation in 5 days out of that in 9 days were improved by proposed method in comparison with Haradas method; (2) the parameter β (which determines the discount rate of curve of circadian rhythm) should be set around 60%, meaning that a raw circadian rhythm (i.e., no discounted rhythm) strongly affected the sleep stage while the highly discounted circadian rhythm (e.g. 30% discounted rhythm) does not contribute to accurately estimating the sleep stage.

Original languageEnglish
Pages297-303
Number of pages7
Publication statusPublished - 2018
Externally publishedYes
Event2018 AAAI Spring Symposium - Palo Alto, United States
Duration: Mar 26 2018Mar 28 2018

Conference

Conference2018 AAAI Spring Symposium
Country/TerritoryUnited States
CityPalo Alto
Period3/26/183/28/18

ASJC Scopus subject areas

  • Artificial Intelligence

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