BADGER Lab grad Weixin Wang, M.S. published a paper on new methods to make sense of real-world data collected with wearable sensors. The key to the new method is to track a person’s location using pedestrian dead-reckoning, and then compare only those movements that occur in repeated circumstances (i.e., locations). Weixin’s paper shows that this method reduces the variability in data used to compare across experimental conditions. He also found some unexpected differences between wearing shoes and wearing sandals!
The paper appears in Sensors (Basel): Analyzing Gait in the Real World Using Wearable Movement Sensors and Frequently Repeated Movement Paths