2022 Fiscal Year Final Research Report
A Bayesian Biomedical Signal Processing for Aging Society
| Project/Area Number |
16K16392
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Biomedical engineering/Biomaterial science and engineering
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| Research Institution | International Christian University (2019-2022)
Aoyama Gakuin University (2016-2018) |
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Principal Investigator |
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| Project Period (FY) |
2016-04-01 – 2023-03-31
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| Keywords | 高齢社会デザイン / 生体信号 / 機械学習 / ベイズ学習 |
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| Outline of Final Research Achievements |
To improve the quality of life of an increasing number of elderly single-person households, it is necessary to consider both (i) physical health care and (ii) mental health care. In this study, we aimed to construct (a) an unconstrained biometric information extraction algorithm using a microwave Doppler sensor for physical health management and (b) an anxiety scale estimation algorithm using an optical topography device for mental health management. Since these signals are affected by noise such as individual differences and environmental factors, we constructed a machine learning algorithm to extract the information.
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| Free Research Field |
生体信号機械学習システム研究
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| Academic Significance and Societal Importance of the Research Achievements |
身体的な健康管理と精神的な健康管理の両方を目的として生体から得られる様々な信号から情報抽出を試みた。その結果無拘束で転倒の検知や心音、心拍、呼吸の測定、拘束性がありながらも血圧や血糖の推定、尿意の予測などの成果が得られた。また脳血流を測定することにより内的な不安、記憶の状態などを推定することが可能となった。
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