Toward a Smart Lower-limb Wearable Interface for Recognition of Gait Phases and Assistance in Level Walking

Peripheral nerve injury often impairs dorsiflexion, leading to asymmetrical gait and increased metabolic cost. While passive ankle-foot orthoses (AFOs) remain common in clinical use, their static, non-adaptive nature limits rehabilitation. Existing active orthoses face challenges such as unreliable gait transition detection, suboptimal actuation, poor generalization, and lack of open-sourcing. This work presents a smart, wearable interface featuring a reproducible design and Bowden cable transmission. A lightweight Bayesian framework enables robust real-time gait transition detection within robot operating system (ROS). The system employs phase-dependent control via a finite state machine, modulating ankle impedance based on gait events. Validation on three unseen users walking naturally demonstrated up to 25% dorsiflexion assistance and phase recognition accuracies of 99.21% (seen interfaces) and 98.75% (unseen), highlighting the system's adaptability. © 2025 IEEE.