Development of a Mixed-Control Ankle Assist Device with Sensor-Fusion-Based Phase Recognition for Walking Exercise Promotion
Chang-Wen Wang, Donglin WANG, Huan WANG, Shuo YAN, Keisuke Osawa, Kei Nakagawa, Eiichiro Tanaka
AI summary
Problem
Existing wearable ankle assist devices often rely on rigid single-mode control, failing to adapt to natural gait variability and causing discomfort or increased physiological effort for frail elderly users.
Approach
The system fuses inertial and plantar-pressure sensor data, optimized via Particle Swarm Optimization, to robustly recognize five gait phases in real time. A dynamic controller then switches between speed, torque, and free assist modes based on the detected phase to match the user's cadence.
Key results
- Improved gait phase recognition accuracy from 57.5% to 70.6% using PSO-optimized sensor fusion
- Increased walking distance from 251 m to 282 m under mixed-mode control
- Reduced heart rate change from 20% to 10%, indicating lower cardiovascular strain
- Enhanced stride length and stabilized cadence compared to single-mode and unassisted baselines
Why it matters
Offers a practical, adaptive control framework for wearable ankle assist devices that safely promotes sustained walking exercise and reduces fatigue in elderly rehabilitation and daily mobility support.
Abstract
“Frail” elderly often experience walking impair- ments that limit independence and sustained physical activity. Although various assistive devices exist, many rely on single- mode control, limiting adaptability, responsiveness to gait vari- ability, and voluntary motion. To improve, we developed a wear- able ankle-assist device with real-time gait phase recognition and multi-mode control. Sensor fusion of inertial and plantar- pressure data enables robust five-phase segmentation, with optimal weights tuned by Particle Swarm Optimization. Based on detected gait phase, the controller dynamically switches between speed, torque, and free modes, adapting to cadence variations. Treadmill experiments showed that mixed control increased walking distance (251 m to 282 m (p < 0.05)), reduced heart rate change (20% to 10% (p < 0.01)). Gait analysis confirmed comfort and less resistance. These findings demonstrate that phase-aware adaptive assistance balances propulsion and natural motion, supporting mobility and re- ducing strain. This framework provides a practical basis for wearable ankle-assist systems in elderly rehabilitation and daily use.