Development of methods for integrated analysis of multiple types of continuous data for behavioural-physiological understanding of health states
| Project/Area Number |
19K22878
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| Research Category |
Grant-in-Aid for Challenging Research (Exploratory)
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| Allocation Type | Multi-year Fund |
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| Review Section |
Medium-sized Section 61:Human informatics and related fields
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| Research Institution | Osaka University |
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Principal Investigator |
Kobayashi Yo 大阪大学, 大学院基礎工学研究科, 准教授 (50424817)
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| Co-Investigator(Kenkyū-buntansha) |
吉田 さちね 東邦大学, 医学部, 講師 (90513458)
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| Project Period (FY) |
2019-06-28 – 2023-03-31
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| Project Status |
Completed (Fiscal Year 2022)
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| Budget Amount *help |
¥6,500,000 (Direct Cost: ¥5,000,000、Indirect Cost: ¥1,500,000)
Fiscal Year 2021: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2020: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2019: ¥2,600,000 (Direct Cost: ¥2,000,000、Indirect Cost: ¥600,000)
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| Keywords | 生体情報処理 / 生体データ / 行動生理学 / 筋硬度 / 生体計測 |
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| Outline of Research at the Start |
日々の健康状態（体調の良し悪し）を定量化しながら，「概ね健康」の定義や維持メカニズムを明らかにする試みであり，新しい解析技術の構築により，生体内の行動生理的な変化を可視化する．
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| Outline of Final Research Achievements |
A generally healthy normal state is, in terms of behavioural physiology, a state in which the various types of biosignal are balanced. Therefore, it is essential to analyse qualitatively different time series data of information in an integrated manner. In this study, an information processing method was developed that, in principle, can input multiple qualitatively different types of biosignal and obtain multiple types of information as output. Its use in biosignal processing was also verified.
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| Academic Significance and Societal Importance of the Research Achievements |
開発した情報処理の実証においては、例として、活動量から心拍数が推定することができる可能性が示唆された。これらの成果は、今後の質的に異なる時系列の生体情報を統合的に解析する手法の構築に活かされていく。さらには、生体計測データを用いたリアルタイムの自動健康診断などでの健康促進や予防検診等において、普段の状態に体調を維持するための健康支援技術に繋がっていく。
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Report
(5 results)
Research Products
(5 results)
