Yanggang Feng
Papers
16
Total Citations
312
H-Index
9
About
Yanggang Feng is a leading researcher in the field of robotic prosthetics and human–machine interaction, with a core focus on developing intelligent, lightweight lower-limb assistive devices for amputees. His work spans locomotion mode recognition, volitional myoelectric control, and energy-efficient prosthesis design. Feng’s most impactful contribution is a multi-level real-time on-board system for recognizing continuous locomotion modes, enabling seamless transitions between six steady modes and ten gait transitions—a breakthrough cited over 65 times. He also pioneered a lightweight motor-driven transtibial prosthesis that combines push-off power with nonlinear damping, and introduced vibrotactile feedback to close the control loop for amputee users. Notably, his 2020 work on energy regeneration from electromagnetic induction during walking achieved self-charging capability in a 1.3 kg robotic prosthesis, a significant step toward autonomous wearable devices. With over 280 cumulative citations across his top ten papers, Feng has also advanced gait-symmetry optimization through human-in-the-loop methods and developed innovative sensing techniques, including strain-gauge-based CNN recognition and carbon-optic fiber sensors for muscle monitoring. His recent work on power-free knee rehabilitation robots for home-based isokinetic training further underscores his commitment to accessible, practical rehabilitation technology.
Research Focus
Key Achievements
Top Papers
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- 7Power-free knee rehabilitation robot for home-based isokinetic training14 citations · 2025
- 8Using One Strain Gauge Bridge to Detect Gait Events for a Robotic Prosthesis13 citations · 2019
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