title: Analysis of time-series correlation between weighted lifestyle data and health data.
abstract: The time-series data analysis described here is based on the simple idea that the accumulation of the effects of lifestyle events, such as ingestion and exercise, could affect personal health with some delay. The delay may reflect complex bio-reactions such as those of metabolism in a human body. In the analysis, the accumulation of the effects of lifestyle events is represented by a summation of daily lifestyle data whose time-series correlation to variations of health data is examined (healthcare-data-mining). The concept of weighting is introduced for the summation of daily lifestyle data. As a result, it is suggested that the nature of personal health could be represented by a weighting pattern characterized by a small number of parameters.
authors.affiliation: Scientific Research, Japanese Ministry of Education, Culture, Sports, Science and Technology. htakeuchi@ takasaki-u.ac.jp
authors.forename: Hiroshi
authors.initials: H
authors.lastname: Takeuchi
authors.forename: Yuuki
authors.initials: Y
authors.lastname: Mayuzumi
authors.forename: Naoki
authors.initials: N
authors.lastname: Kodama
mesh_terms: D056044:Actigraphy / Q000379:methods*; D000203:Activities of Daily Living; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D015438:Health Behavior; D006304:Health Status; D006305:Health Status Indicators; D006801:Humans; D008019:Life Style; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D013223:Statistics as Topic