Fluctuations in step counts derived from accelerometer data
Keywords:
fitness tracking, signal processing, algorithmsAbstract
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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