Sleep stage estimation by specifying latent structure of heartbeat data
Project/Area Number |
15K12105
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Research Category |
Grant-in-Aid for Challenging Exploratory Research
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Allocation Type | Multi-year Fund |
Research Field |
Soft computing
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Research Institution | The University of Electro-Communications |
Principal Investigator |
TAKADAMA Keiki 電気通信大学, 大学院情報理工学研究科, 教授 (20345367)
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Project Period (FY) |
2015-04-01 – 2017-03-31
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Project Status |
Completed (Fiscal Year 2016)
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Budget Amount *help |
¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2016: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2015: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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Keywords | ソフトコンピューティング / 機械学習 / 睡眠段階推定 / 人工知能 |
Outline of Final Research Achievements |
This research focuses on the sleep stage estimation method without connecting any devices to human body, and improves its estimation capability even in bad health condition, aging process, and sleep disorder. Since a sleep rhythm or deepness is affected by health condition, aging, and/or sleep disorder, this research proposed the approach of mining the latent structure of heartbeat data (called the sleep property) to specify the common sleep property as a combination of the frequency components of the ultradian rhythm (i.e., a cycle of non-REM and REM sleep) derived from the heartbeat data. To investigate the effectiveness of the proposed approach, we conducted the human subject experiments which revealed that the improved sleep stage estimation method based on the proposed approach is robust to bad health condition, adapts to aging, and copes with sleep disorder.
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Report
(3 results)
Research Products
(23 results)
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[Journal Article] Evolutionary algorithms for uncertain evaluation functions,2015
Author(s)
Tajima, Y., Nakata, M., Matsushima, H., Sato, H., Hattori, K., and Takadama, K.
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Journal Title
New Mathematics and Natural Computation,World Scientific
Volume: Vol. 11
Issue: 02
Pages: 201-215
DOI
Related Report
Peer Reviewed
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[Presentation] Real-time Sleep Stage Estimation from Biological Data with Trigonometric Function Regression Model2016
Author(s)
Harada, T. ( Uwano, F., Komine, T., Tajima, Y., Kawashima, T.)
Organizer
The AAAI 2016 Spring Symposia, Well-Being Computing: AI Meets Health and Happiness Science, AAAI (The Association for the Advancement of Artificial Intelligence)
Place of Presentation
Stanford, USA
Year and Date
2016-03-22
Related Report
Int'l Joint Research
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[Presentation] Effects on Sleep by `Cradle Sound' Adjusted to Heartbeat and Respiration2016
Author(s)
Morishima, M.(Sugino, Y., Ueya, Y., Kadotani, H., and Takadama, K)
Organizer
The AAAI 2016 Spring Symposia, Well-Being Computing: AI Meets Health and Happiness Science, AAAI (The Association for the Advancement of Artificial Intelligence)
Place of Presentation
Stanford, USA
Year and Date
2016-03-22
Related Report
Int'l Joint Research
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