Adaptive Oscillator-Based Gait Feature Extraction Method of Hip Exoskeleton for Stroke Patients

For a lower-limb exoskeleton, accurate and timely extraction of gait features, such as the timing of important gait events and walking state transitions, is a fundamental requirement to provide appropriate assistive action, and this becomes much more challenging for stroke patients due to the existence of hemiplegic gait. In view of this, this study develops an adaptive oscillator-based gait feature extraction method only using thigh-worn inertial measurement units (IMUs) for assisting stroke patients with portable hip exoskeletons. The algorithm is capable of 1) estimating the zero position of the thigh during locomotion, 2) estimating the timing of heel strike, and 3) detecting the walking state transition timely. To validate the proposed method, an experimental study with both healthy subjects and stroke patients has been performed, suggesting accurate estimations of the zero position of the thigh and the timing of heel strike, and a lower detection delay of walking state transitions compared to state-of-the-art studies. To the best of the authors' knowledge, this study represents the first proof of feasibility to extract these gait features of stroke patients with hemiplegic gait only using thigh-worn IMUs, paving the way for future clinical applications of portable hip exoskeletons.