Chengchen Wang
Papers
1
Total Citations
5
H-Index
1
About
Chengchen Wang is a leading researcher in rehabilitation robotics and human-robot interaction, with a focus on developing intelligent control systems for upper limb rehabilitation. Wang’s most-cited work, "Control Strategy for Upper Limb Rehabilitation Robot Based on Muscle Strength Estimation" (2020), addresses a critical challenge in active rehabilitation for hemiplegic patients: enabling robots to respond intuitively to a patient’s voluntary effort. By integrating surface electromyography (sEMG) signal filtering and muscle strength estimation, Wang’s proposed control strategy allows rehabilitation robots to adapt their assistance in real time, fostering more natural and effective patient-robot collaboration. This contribution bridges biosignal processing and robotic control, advancing personalized therapy for stroke survivors. With 5 citations, the paper has informed subsequent studies on adaptive exoskeletons and assistive devices. Wang’s work stands out for its practical focus on active training modes, where patient engagement is paramount. By combining biomechanics, signal processing, and control theory, Wang is helping to shape a new generation of rehabilitation technologies that are safer, more responsive, and tailored to individual recovery needs.
Research Focus
Key Achievements
Top Papers
- 1