Stance phase detection for walking and running using an IMU periodicity-based approach

Abstract

This paper presents a novel stance phase detection procedure based on observations from a foot-mounted inertial measurement unit (IMU). A frequency-tracking algorithm from the field of audio analysis was applied to the inertial signal to obtain information about gait cycle duration. Afterwards, this information was used to determine the stance phase point for the next gait cycle. This periodicity-based stance-phase detection procedure was found to be superior to traditional thresholdbased algorithms, significantly reducing the number of insertion and deletion errors, with less dependence on selected threshold values.