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 |
Research Field |
Biomedical engineering/Biomaterial science and engineering
|
Research Institution | International Christian University (2019-2022) Aoyama Gakuin University (2016-2018) |
Principal Investigator |
|
Project Period (FY) |
2016-04-01 – 2023-03-31
|
Project Status |
Completed (Fiscal Year 2022)
|
Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000)
Fiscal Year 2019: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2018: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2017: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2016: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
|
Keywords | 高齢社会デザイン / 生体信号 / 機械学習 / ベイズ学習 / マイクロ波ドップラーセンサ / 自己符号化器 / ベイジアンネットワーク / 無拘束生体情報 / 不安尺度 / 隠れマルコフモデル / 不安尺度推定 / サポートベクターマシン / 動的時間伸縮法 / 計測工学 / 人工知能 / 生体信号処理 |
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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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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Report
(8 results)
Research Products
(103 results)