top of page
AI pixabay huge.jpg

“one-size-fits-most” walking recognition method for smartphones, watches, wearable accelerometers

We propose a walking recognition method for sub-second tri-axial accelerometer data, in which activity classification is based on the inherent features of walking: intensity, periodicity, and duration. We validate our method against 20 publicly available, annotated datasets on walking activity data collected at various body locations (thigh, waist, chest, arm, wrist).


bottom of page