Time Series Clustering Analysis of Health-Promoting Behavior

被引:0
作者
Yang, Chi-Ta [1 ]
Hung, Yu-Shiang [1 ]
Deng, Guang-Feng [1 ]
机构
[1] Inst Informat Ind, Innovat DigiTech Enabled Applicat & Serv Inst, Taipei 105, Taiwan
来源
11TH INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS 2013, PTS 1 AND 2 (ICNAAM 2013) | 2013年 / 1558卷
关键词
Time series mining; health promotion; fuzzy c-mean clustering; pattern discovery; SELF-CARE; OLDER-ADULTS; MODEL;
D O I
10.1063/1.4825962
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
Health promotion must be emphasized to achieve the World Health Organization goal of health for all. Since the global population is aging rapidly, ComCare elder health-promoting service was developed by the Taiwan Institute for Information Industry in 2011. Based on the Pender health promotion model, ComCare service offers five categories of health-promoting functions to address the everyday needs of seniors: nutrition management, social support, exercise management, health responsibility, stress management. To assess the overall ComCare service and to improve understanding of the health-promoting behavior of elders, this study analyzed health-promoting behavioral data automatically collected by the ComCare monitoring system. In the 30638 session records collected for 249 elders from January, 2012 to March, 2013, behavior patterns were identified by fuzzy c-mean time series clustering algorithm combined with autocorrelation-based representation schemes. The analysis showed that time series data for elder health-promoting behavior can be classified into four different clusters. Each type reveals different health-promoting needs, frequencies, function numbers and behaviors. The data analysis result can assist policymakers, health-care providers, and experts in medicine, public health, nursing and psychology and has been provided to Taiwan National Health Insurance Administration to assess the elder health-promoting behavior.
引用
收藏
页码:2147 / 2150
页数:4
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