| Project/Area Number |
15H03095
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Applied health science
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| Research Institution | Osaka University (2017)
The University of Tokyo (2015-2016) |
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Principal Investigator |
Nakamura Toru 大阪大学, 基礎工学研究科, 特任教授(常勤) (80419473)
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| Co-Investigator(Kenkyū-buntansha) |
山本 義春 東京大学, 大学院教育学研究科(教育学部), 教授 (60251427)
早野 順一郎 名古屋市立大学, 大学院医学研究科, 教授 (90173054)
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| Project Period (FY) |
2015-04-01 – 2018-03-31
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| Project Status |
Completed (Fiscal Year 2017)
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| Budget Amount *help |
¥15,990,000 (Direct Cost: ¥12,300,000、Indirect Cost: ¥3,690,000)
Fiscal Year 2017: ¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2016: ¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2015: ¥7,670,000 (Direct Cost: ¥5,900,000、Indirect Cost: ¥1,770,000)
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| Keywords | 加齢・老化 / フレイル / 動的恒常性 / 身体活動 / フレイルティ / ホルター心電図 |
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| Outline of Final Research Achievements |
We aimed at developing a new quantification method of frailty using a large-scale database (about 100,000) of heart rate variability and body acceleration data measured by 24-hour Holter electrocardiogram in daily life. We demonstrated the dependency of total amount of physical activity on age, gender, region, and seasonality. We then proposed the index, “physical activity age", derived from the factors influencing total amount of physical activity, and further examined the relationship with frailty. We also obtained sleep epidemiological knowledge by developing the sleep-wake discrimination algorithm. Further, the classification of daily living behaviors by using deep learning approaches was conducted. These could be useful for evaluating frailty in elder people.
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