2006 Fiscal Year Final Research Report Summary
Personal Dynamic Healthcare System Utilizing Mobile Phone and Web technologies
| Project/Area Number |
16500457
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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 |
Applied health science
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| Research Institution | Takasaki University of Health and Welfare |
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Principal Investigator |
TAKEUCHI Hiroshi Takasaki University of Health and Welfare, Faculty of Health and Welfare, Professor, 健康福祉学部, 教授 (00348129)
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| Project Period (FY) |
2004 – 2006
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| Keywords | Personal healthcare system / Mobile phone / Web technology / Healthcare data mining / Association rule mining / Lifestyle data / Health data |
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| Research Abstract |
2004
Personal dynamic healthcare system utilizing mobile phone and web technologies was developed for preventing diseases and improving wellness. In this system, daily health and lifestyle data inputted through a mobile phone are transferred to a web application server via the Internet. A web application server provides data archiving and reference services visualizing health and lifestyle data graphically on a mobile phone display, and a data mining service notifying users some important rules between health data and lifestyle data.
2005
Automated healthcare-data-mining processes, which extract rules correlating health and lifestyle data, were studied. The concept behind healthcare data mining is extracting personally useful information, such as rules and patterns concerning lifestyles and health conditions, embedded in daily time-series personal health and lifestyle data. These data were stored on a developed personal dynamic healthcare system utilizing mobile phone and web technologies. An automated healthcare-data mining for the stored time-series data of volunteer users generated some useful rules correlating lifestyles with blood pressure and body-fat index.
2006
The healthcare-data-mining presented here extracts personally useful information, such as rules and patterns concerning lifestyles and health conditions, from daily time-series personal health and lifestyle data stored on a personal dynamic healthcare system by using mobile phone and web technologies. This year, studies focused on time-series data analyses in the healthcare-data-mining process. Interesting results concerning the relation between lifestyles (soybean protein ingestion, energy expenditure due to exercise, ingestion at meal) and health conditions (body-fat percentage, basal metabolism, blood pressure) were obtained.
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