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Mathematical Problems in Engineering
Volume 2015 (2015), Article ID 618061, 11 pages
http://dx.doi.org/10.1155/2015/618061
Research Article

Applying Data Mining Techniques to Identify Suitable Activities

1Sports Information and Communication, Aletheia University, New Taipei City 25103, Taiwan
2Information Engineering, Kun Shan University, Tainan 71003, Taiwan

Received 13 August 2015; Revised 6 October 2015; Accepted 8 October 2015

Academic Editor: Meng Du

Copyright © 2015 Yu-Fang Yeh and Ching-Pao Chang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Identifying suitable physical activities is crucial for personal health management. However, a big challenge in identifying suitable physical activities is the influencing factors are extremely complex. Therefore, this study aims to propose an approach to facilitate the construction of suitable physical activity models. In the approach, association rule mining and clustering technique are applied to analyze personal activity-physiological information. To demonstrate how the proposed approach can be used for constructing the activity models, an experiment using mobile devices to collect personal activity-physiological information was designed. The revealed models can be used to not only understand personal health conditions but also provide useful information about proper and improper physical activities.