| Project/Area Number |
15300210
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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 |
Physical education
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| Research Institution | The University of Tokyo |
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Principal Investigator |
YAMAMOTO Yoshiharu The University of Tokyo, Graduate School of Education, Professor, 大学院教育学研究科, 教授 (60251427)
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| Co-Investigator(Kenkyū-buntansha) |
KUMANO Hiroaki The University of Tokyo, Hospital, Associate Professor, 医学部附属病院, 助教授 (90280875)
久保木 冨房 東京大学, 医学部附属病院, 教授 (40111512)
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| Project Period (FY) |
2003 – 2005
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| Project Status |
Completed (Fiscal Year 2005)
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| Budget Amount *help |
¥11,700,000 (Direct Cost: ¥11,700,000)
Fiscal Year 2005: ¥3,700,000 (Direct Cost: ¥3,700,000)
Fiscal Year 2004: ¥3,500,000 (Direct Cost: ¥3,500,000)
Fiscal Year 2003: ¥4,500,000 (Direct Cost: ¥4,500,000)
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| Keywords | physical activity pattern / psychiatric and psychosomatic disorders / time series analysis |
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| Research Abstract |
The aim of this project was to evaluate the relationship between ecologically measured psychological symptoms and physical activity data in patients with psychiatric and psychosomatic disorders and healthy adolescents, and to develop methods to extract the altered physical activity patterns related to the symptom worsening.
(1)Research on patients with chronic fatigue syndrome (CFS)
We developed a new method based on the wavelet transform to characterize the physical activity time series, which can evaluate the temporal correlation at the interruption of activities by the negative modulus maxima of the transform. We found that up to 35 min the local correlation property was significantly smaller in CFS patients than in controls, suggesting that CFS patients have more abrupt interruptions of physical activity.
(2)Research on junior high school students
We found that subjective moods and fatigue in these subjects had significant correlations with statistical indices calculated from 30 min ac
… More
tivity data before each measurement. In a multiple regression model incorporating statistics of activity data to estimate subjective fatigue, the mean and detrended skewness and their interaction term were highly significant as fatigue estimators. The detrended skewness which is related to abrupt drop or interruption of activities showed the highest significance.
(3)Research on patients with major depression
We found that durations of resting periods having continuously smaller counts than the overall recorded average of activity obey a power-law cumulative distribution over more than two decades (from 2 min to 200 min) in both control subjects and major depression patients. The power-law exponent of major depression patients was significantly smaller than that of healthy individuals, implying more frequent episodes of longer resting periods in the patients.
These results (1)-(3) suggest that psychiatric and psychosomatic symptoms can be quantified and predicted by the statistical parameters at the interruption of physical activity. Less
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