Fluctuations in step counts derived from accelerometer data

  • Lloyd Gabriel T Rizada National Institute of Physics, University of the Philippines Diliman
  • Damian N Dailisan National Institute of Physics, University of the Philippines Diliman
  • May T Lim National Institute of Physics, University of the Philippines Diliman

Abstract

Fitness tracking apps in smartphones measure activities such as step count. However, most app algorithms are hidden from the user, i.e. a blackbox, and what exactly is being measured is not known to the user. This paper implements a step counting algorithm disclosed by Pebble Technology Corporation. We also assessed how the calculated number of steps changed with the wearable (accelerometer) placement. Four mount points were considered: hand, arm, pocket, and ankle; while two activities: walking and running were analyzed. Step counts by the Pebble algorithm deviated from actual values by less than 20% the actual values. Running has generally better step counting estimates than walking (except on the ankle). An ankle placement yielded the most accurate walking measurement, while a hand placement had the closest measurement for running.

Published
2017-06-07
How to Cite
[1]
L. G. Rizada, D. Dailisan, and M. Lim. Fluctuations in step counts derived from accelerometer data, Proceedings of the Samahang Pisika ng Pilipinas 35, SPP-2017-1D-03 (2017). URL: https://paperview.spp-online.org/proceedings/article/view/97.
Section
Complex Systems and Data Analytics