Development for automatic diagnosis system for health condition, using entropy of behavior information
| Project/Area Number |
18500444
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Rehabilitation science/Welfare engineering
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| Research Institution | Osaka Electro-Communication University |
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Principal Investigator |
NAMBU Masayuki Osaka Electro-Communication University, Faculty of Biomedical Engineering, Associate Professor (10333395)
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| Project Period (FY) |
2006 – 2007
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| Project Status |
Completed (Fiscal Year 2007)
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| Budget Amount *help |
¥4,020,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥420,000)
Fiscal Year 2007: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Fiscal Year 2006: ¥2,200,000 (Direct Cost: ¥2,200,000)
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| Keywords | Home care / Biomedical measurement / Network / Bluetooth / Entropy |
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| Research Abstract |
In the first year, I developed measurement systems and software for data acquisition and analysis.
The measurement system consists of infrared sensors, wired and wireless network systems, and Bluetooth wireless communication device. I also developed the mobile type sensor system using accelerometer and Bluetooth wireless communication device. In the traditional system, the measurement system has problem of the size and energy consumption. In the developed system, I reduce the thickness of the device for the portability. As the result of improvement, the time for measurement is extended. In addition, I can acquire the data of the subject on the Internet, because I developed the data acquisition software on the WWW system. Furthermore, I developed an algorithm to acquire the entropy from long term data.
In the second year, I verified utility and the validity of the developed system. In this year I acquired the long term data of the behavior in the daily life. In addition, I analyze the long term data First I adopt the traditional linear method for comparison. However I found the unusual points of data, I could not found the significant difference between usual data and unusual data. Second, I acquired the indexes using entropy of long time data. I found the significant difference between the indexes from usual and unusual state. This result was corresponding to the result of questionnaire survey. As the result, the effectiveness of the proposal technique was suggested.
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Report
(3 results)
Research Products
(12 results)
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[Presentation] 位置センサの反応頻度からの健康状態推定2007
Author(s)
南部 雅幸, 岡田 和也
Organizer
計測自動制御学会システム情報部門学術講演会
Place of Presentation
国立オリンピック青少年総合センター,東京
Year and Date
2007-11-26
Description
「研究成果報告書概要(和文)」より
Related Report
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