Analysis of time-series correlation between weighted lifestyle data and health data

Author

Takeuchi, Hiroshi ; Mayuzumi, Yuuki ; Kodama, Naoki

Author_Institution

Dept. of Healthcare Inf., Takasaki Univ. of Health & Welfare, Takasaki, Japan

fYear

2011

fDate

Aug. 30 2011-Sept. 3 2011

Firstpage

1511

Lastpage

1514

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.

Keywords

biomechanics; data mining; health care; time series; bioreactions; delay; exercise; health data; healthcare data mining; ingestion; metabolism; personal health; time series correlation; weighted lifestyle data; Conferences; Correlation; Data mining; Delay; Educational institutions; Informatics; Medical services; Actigraphy; Activities of Daily Living; Computer Simulation; Data Interpretation, Statistical; Health Behavior; Health Status; Health Status Indicators; Humans; Life Style; Male; Middle Aged; Models, Statistical; Statistics as Topic;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE

Conference_Location

Boston, MA

ISSN

1557-170X

Print_ISBN

978-1-4244-4121-1

Electronic_ISBN

1557-170X

Type

conf

DOI

10.1109/IEMBS.2011.6090345

Filename

6090345