Gait Event Detection From Thigh Segment Kinematics in Children With Crouch Gait

OBJECTIVE: Wearable exoskeletons can improve walking in children with movement disorders by delivering precisely timed and scaled torques based on discrete gait phase. Most single-joint systems segment the gait cycle using underfoot force-sensitive resistors (FSRs), but FSRs are suboptimal for exoskeleton use in pathological gait due to fragile hardware and inconsistent foot loading/unloading. Thigh kinematics may provide more robust gait event detection (GED), yet this approach has not been evaluated in children with crouch gait, a key target population for pediatric exoskeleton therapy. This study aimed to: 1) assess feasibility of GED using thigh kinematics from ground-truth motion capture, 2) evaluate GED using a thigh-mounted inertial measurement unit (IMU), and 3) validate this method with a wearable knee exoskeleton in children with crouch gait. METHODS AND PROCEDURES: A novel thigh segment kinematics algorithm (TSKA) was developed to detect initial contact (IC) and terminal contact (TC) during overground walking. Algorithm performance was assessed using IMU-derived gait events compared to motion capture ground truth, then evaluated with a wearable knee exoskeleton. RESULTS: Mean IMU-based timing errors for IC and TC were 38 and 84 ms, respectively. IC predictions occurred earlier than ground truth, whereas TC predictions varied. During exoskeleton walking, IMU-based GED significantly improved timing accuracy compared to FSR-based detection. CONCLUSION: The thigh-based kinematic algorithm, tuned for each individual with six or fewer strides, accurately detected gait events in children with crouch gait and outperformed FSR-based GED in an exoskeleton. These findings support further development for real-time exoskeleton control and gait assessment in individuals with pathological gait.