Liuni Qin
Papers
1
Total Citations
58
H-Index
1
About
Dr. Liuni Qin is a leading researcher at the intersection of human-machine interaction and neural engineering, with a primary focus on decoding dexterous motor intent from surface electromyography (sEMG) signals. Her most impactful work introduces a novel CNN-Attention network architecture for the continuous estimation of finger kinematics, a breakthrough that enables simultaneous and proportional control of robotic hands for both industrial and rehabilitation applications. This highly cited paper (58 citations) addresses a critical challenge in the field: achieving precise, real-time finger movement prediction from muscle activity. By integrating convolutional neural networks with attention mechanisms, Dr. Qin’s approach significantly improves estimation accuracy, advancing the development of intuitive prosthetic limbs and exoskeletons. Her contributions are pivotal for restoring natural motor function in individuals with limb loss or neurological impairments, and her work is widely recognized for bridging deep learning techniques with practical biomedical engineering solutions. Dr. Qin’s research continues to push the boundaries of how human intent can be translated into seamless robotic control.
Research Focus
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Top Papers
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