| Project/Area Number |
25880010
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| Research Category |
Grant-in-Aid for Research Activity Start-up
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| Allocation Type | Single-year Grants |
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| Research Field |
Intelligent informatics
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| Research Institution | Yokohama National University |
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Principal Investigator |
SUZUKI TAKUO 横浜国立大学, 工学(系)研究科(研究院), 研究教員 (80709303)
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| Project Period (FY) |
2013-08-30 – 2015-03-31
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| Project Status |
Completed (Fiscal Year 2014)
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| Budget Amount *help |
¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
Fiscal Year 2014: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2013: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | モバイルヘルス / 健康管理 / 物体検出 / 画像処理 / 状態推定 / 行動認識 / 人間支援システム / 人間計測システム / 異常検知 / パターン認識 / 服薬管理 / 服薬指導 / 遠隔見守り / チーム医療支援 |
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| Outline of Final Research Achievements |
In this research, an original algorithm that predicts the future state of recipient’s activity was developed to detect a medication error (e.g. a recipient occasionally overdoses or forgets to take medicine) while going out. The future state was estimated based on data measured by a variety of sensors in a smartphone such as an acceleration sensor, a gyro sensor, an ambient light sensor, a touch panel, and a barometer. The data were converted to feature quantities, which do not correlate with each other, by principal component analysis and were entered into a Bayesian network for activity state estimation. The target value of accuracy of estimation was set more than 70 percent, but it was not achieved. The main reason of the bad result was that eating-related states were so difficult to be predicted only by using the above sensors.
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