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Contextual motivation in physical activity by means of association rule mining
Egyptian Informatics Journal
  • Sugam Sharma, Iowa State University
  • Udoyara Sunday Tim, Iowa State University
  • Marinelle Payton, Jackson State University
  • Hari Cohly, Jackson State University
  • Shashi Gadia, Iowa State University
  • Johnny Wong, Iowa State University
  • Sudharshanam Karakala, Jackson State University
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The primary thrust of this work is to demonstrate the applicability of association rule mining in public health domain, focusing on physical activity and exercising. In this paper, the concept of association rule mining is shown assisting to promote the physical exercise as regular human activity. Specifically, similar to the prototypical example of association rule mining, market basket analysis, our proposed novel approach considers two events – exercise (sporadic) and sleep (regular) as the two items of the frequent set; and associating the former, exercise event, with latter, the daily occurring activity sleep at night, helps strengthening the frequency of the exercise patterns. The regularity can further be enhanced, if the exercising instruments are kept in the vicinity of the bed and are within easy reach.

This article is from Egyptian Informatics Journal 16 (2015): 243–251, doi:10.1016/j.eij.2015.06.003. Posted with permission.

This work is licensed under a Creative Commons CC-BY-NC-ND 4.0 license.
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Sugam Sharma, Udoyara Sunday Tim, Marinelle Payton, Hari Cohly, et al.. "Contextual motivation in physical activity by means of association rule mining" Egyptian Informatics Journal Vol. 16 Iss. 3 (2015) p. 243 - 251
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