Gait Phase Detection of Exoskeleton Robot Based on the Joints Angle of Lower Limb

Abstract

The lower limb exoskeleton robot is a wearable device that enhances the human lower extremity movement ability. And gait phase detection is an important prerequisite for controlling the lower limb exoskeleton robot. Traditional gait phase detection is mostly based on ground contact forces (GCFs) measured by force sensitive resistors (FSRs). However, FSRs will lose its lifespan and accuracy due to the impact force generated by gait. In view of this shortcoming, a gait phase detection method based on the joints angle of lower limb is proposed. Stacked LSTMs was constructed by using joints angle information of lower limb exoskeleton as input and gait phase as output. Through the experimental analysis of the different wearers' gait phase detection results, Stacked LSTMs could effectively detect the gait phase through the joints angle information with an average accuracy rate of 94.1%, which has a certain role in simplifying the exoskeleton robot sensor network.