Early recognition of gait initiation and termination using wearable sensors

This paper presents an approach for early recognition of gait initiation and termination using wearable inertial measurement units and pressure-sensitive insoles. Body joint angles, ground reaction force and center of plantar pressure of each foot are obtained from these sensors and input into a supervised learning algorithm. For gait initiation, the algorithm detects two events: gait onset (the first detectable change from the baseline state) and toe-off. For gait termination, the algorithm segments gait into different steps, measures the signals over a window at the beginning of each step, and determines whether the measurement belongs to the final step. The approach is validated with 10 subjects at two different gait speeds, with both within-subject and subject-independent crossvalidation. Results show that the inertial measurement units are generally more useful than insoles during both gait initiation and termination, though combining both types of sensors results in better onset detection and easier segmentation of gait into different steps. However, for best performance the algorithms should be trained for each subject separately, and the gait termination recognition algorithm is not very robust with regard to gait speed.