Papers
11
Total Citations
190
H-Index
6
About
Yaqi Chu is a biomedical engineer and human-robot interaction researcher whose work bridges neural signal processing, brain-computer interfaces (BCIs), and rehabilitation robotics. With a body of work spanning EEG-based motor imagery decoding, electromyography (EMG)-driven control systems, and soft robotic exoskeletons, Chu has made meaningful contributions to assistive technologies for individuals with motor impairments. His most influential work, "Decoding multiclass motor imagery EEG from the same upper limb" (2020, 89 citations), tackled the formidable challenge of distinguishing fine-grained limb movements using Riemannian geometry and partial least squares regression — a significant advance for BMI accuracy. His widely read 2024 review on intuitive human-robot-environment interaction with EMG signals (42 citations) synthesizes decades of research while identifying critical gaps between laboratory findings and real-world deployment. Chu has also pioneered novel interface paradigms, including a Face-Computer Interface using facial EMG for limb-impaired users, SSVEP-driven rehabilitation robotics, and bioinspired pneumatic soft exoskeletons for hand rehabilitation. Collectively, his research reflects a commitment to making assistive and rehabilitative technology more natural, accessible, and clinically viable.
Research Focus
Key Achievements
Top Papers
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- 2Intuitive Human-Robot-Environment Interaction with EMG Signals: A Review42 citations · 2024
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