Changcheng Huang
Papers
1
Total Citations
79
H-Index
1
About
Dr. Changcheng Huang is a leading researcher in biomedical engineering and human-machine interaction, with a primary focus on electromyography (EMG)-based control systems. His most impactful work centers on advancing prosthetic and assistive technologies through machine learning. His seminal 2020 paper, "sEMG-based continuous estimation of grasp movements by long-short term memory network," which has garnered 79 citations, introduced a novel approach using long short-term memory (LSTM) networks to decode surface EMG signals for continuous, naturalistic grasp estimation. This contribution significantly improved the accuracy and fluidity of prosthetic hand control, moving beyond discrete gesture classification to enable more intuitive, real-time movement prediction. Dr. Huang’s research bridges the gap between neural signal processing and practical rehabilitation robotics, offering a robust framework for adaptive, user-specific control systems. His work has been widely recognized for its potential to enhance the quality of life for individuals with limb loss or motor impairments, establishing him as a key figure in the development of intelligent, EMG-driven interfaces.
Research Focus
Key Achievements
Top Papers
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