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

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.

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.

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.

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.