Journal of Medical Systems

, 38:95

Better Physical Activity Classification using Smartphone Acceleration Sensor

  • Muhammad Arif
  • Mohsin Bilal
  • Ahmed Kattan
  • S. Iqbal Ahamed
Mobile Systems

DOI: 10.1007/s10916-014-0095-0

Cite this article as:
Arif, M., Bilal, M., Kattan, A. et al. J Med Syst (2014) 38: 95. doi:10.1007/s10916-014-0095-0
Part of the following topical collections:
  1. Mobile Systems

Abstract

Obesity is becoming one of the serious problems for the health of worldwide population. Social interactions on mobile phones and computers via internet through social e-networks are one of the major causes of lack of physical activities. For the health specialist, it is important to track the record of physical activities of the obese or overweight patients to supervise weight loss control. In this study, acceleration sensor present in the smartphone is used to monitor the physical activity of the user. Physical activities including Walking, Jogging, Sitting, Standing, Walking upstairs and Walking downstairs are classified. Time domain features are extracted from the acceleration data recorded by smartphone during different physical activities. Time and space complexity of the whole framework is done by optimal feature subset selection and pruning of instances. Classification results of six physical activities are reported in this paper. Using simple time domain features, 99 % classification accuracy is achieved. Furthermore, attributes subset selection is used to remove the redundant features and to minimize the time complexity of the algorithm. A subset of 30 features produced more than 98 % classification accuracy for the six physical activities.

Keywords

Smartphone Acceleration Physical Activity Classification Healthcare 

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Muhammad Arif
    • 1
  • Mohsin Bilal
    • 1
  • Ahmed Kattan
    • 1
  • S. Iqbal Ahamed
    • 2
  1. 1.Department of Computer Science College of Computer and Information systemsUmm-Alqura UniversityMakkahSaudi Arabia
  2. 2.Ubicomp Lab Department of Mathematics, Statistics and Computer ScienceMarquette UniversityMilwaukeeUSA

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