Yao Chou
Papers
2
Total Citations
9
H-Index
2
About
Yao Chou is a researcher working at the intersection of intelligent robotics, human-robot interaction (HRI), and computer vision. His work focuses on developing robust control strategies for upper limb rehabilitation and industrial applications, particularly through the integration of bio-signals and advanced neural dynamics. Chou’s most cited paper (2023, 6 citations) introduces a novel anti-disturbance zeroing neurodynamic strategy driven by surface electromyogram (sEMG) signals, leveraging the “artificial systems, computational experiments, and parallel execution” (ACP) framework to enhance HRI control under real-world disturbances. This work addresses critical challenges in adaptive, human-centered robotic assistance. Earlier, Chou contributed to 3D computer vision with a parallel convolutional neural network (CNN) architecture for stereo vision estimation (2017, 3 citations), prioritizing real-time performance for robotics and unmanned vehicles. While his citation counts are modest, his research demonstrates a clear trajectory toward practical, bio-inspired control systems that bridge neural computation and physical interaction. Chou’s work is particularly relevant for students and researchers interested in rehabilitation robotics, neural control, and vision-based autonomy.
Research Focus
Key Achievements
Top Papers
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