Papers
2
Total Citations
72
H-Index
2
About
Haoyi Zhao is a researcher in rehabilitation robotics and human–machine interaction, with a focus on surface electromyography (sEMG) signal processing and intelligent control systems. His work addresses critical challenges in assistive technology, particularly in gesture recognition for rehabilitation robots and precision control of robotic manipulators. In his most cited study (65 citations), Zhao developed a multi-object intergroup gesture recognition method using fusion features and a K-nearest neighbor (KNN) algorithm, introducing a novel feature extraction technique based on activated muscle regions from sEMG signals—a significant step toward more intuitive and responsive human–computer interfaces for medical and assistive applications. He also advanced trajectory tracking for assembly robots by designing a self-tuning fuzzy PID controller that adapts quantification and proportionality factors, improving system robustness and tracking accuracy under external disturbances. Zhao’s work bridges bioelectrical signal analysis and adaptive control theory, contributing to more reliable and efficient robotic systems. His research holds promise for enhancing the quality of life for individuals with motor impairments and for advancing automation in precision manufacturing.
Research Focus
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Top Papers
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