Papers
11
Total Citations
198
H-Index
7
About
Daohui Zhang is a leading researcher in bio-inspired robotics and human-machine interaction, specializing in electromyography (EMG) signal processing, tactile sensing, and soft robotic systems. His work bridges the gap between neural control and robotic actuation, with major contributions in EMG pattern recognition for prosthetic hands—his 2014 comparative study on PCA and LDA for anthropomorphic hand control has garnered 57 citations and remains foundational in the field. Zhang’s 2024 review on intuitive human-robot-environment interaction using EMG signals (42 citations) synthesizes decades of progress, highlighting persistent challenges in real-world deployment. He has also pioneered tactile sensing for extreme environments, developing sensors that operate under 50 MPa hydrostatic pressure for deep-sea robotic manipulators (30 citations), and a bioinspired iontronic skin for underwater tactile sensing (2025). His work extends to continuous gait tracking using sEMG (12 citations), facial EMG-based human-computer interfaces for assistive technology (17 citations), and soft pneumatic exoskeletons for hand rehabilitation (9 citations). With over 200 cumulative citations, Zhang’s research is driving the next generation of intuitive, resilient human-robot systems for healthcare, deep-sea exploration, and beyond.
Research Focus
Key Achievements
Top Papers
- 1
- 2Intuitive Human-Robot-Environment Interaction with EMG Signals: A Review42 citations · 2024
- 3
- 4
- 5
- 6Continuous human gait tracking using sEMG signals12 citations · 2020
- 7
- 8
- 9
- 10