Naishi Feng
Papers
7
Total Citations
143
H-Index
4
About
Dr. Naishi Feng is a leading researcher in the intersection of soft robotics, human–robot interaction, and brain–computer interfaces (BCI). Their work focuses on creating intuitive, safe control systems for assistive and service robots. A central contribution is the development of a soft robotic hand—a design that prioritizes safe, human-like interaction—controlled via surface electromyography (sEMG), which has garnered 73 citations. Dr. Feng has further advanced human–robot communication by integrating single-channel EEG signals with end-to-end convolutional neural networks for mobile robot control, and by employing graph Fourier transforms to decode motor imagery for BCI applications. Their research consistently aims to enhance robot autonomy while ensuring human safety, as seen in their work on movement authorization based on attention monitoring. With over 140 total citations across their most-cited works, Dr. Feng’s innovative fusion of soft actuation, neural signal processing, and machine learning is paving the way for more responsive and secure robotic systems in rehabilitation and service contexts.
Research Focus
Key Achievements
Top Papers
- 1A soft robotic hand: design, analysis, sEMG control, and experiment73 citations · 2018
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- 7Humanoid Soft Hand Design Based on sEMG Control2 citations · 2018