Fluctuations in step counts derived from accelerometer data

Authors

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

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Issue

2017: Proceedings of the 35th Samahang Pisika ng Pilipinas Physics Conference

Article ID

SPP-2017-1D-03

Section

Complex Systems and Data Analytics

Published

2017-06-07

How to Cite

[1]

LGT Rizada, DN Dailisan, and MT Lim, Fluctuations in step counts derived from accelerometer data, Proceedings of the Samahang Pisika ng Pilipinas 35, SPP-2017-1D-03 (2017). URL: https://proceedings.spp-online.org/article/view/SPP-2017-1D-03.