Papers
1
Total Citations
7
H-Index
1
About
Dr. Jingsong Mu is a leading researcher in biomedical signal processing and human-machine interaction, with a primary focus on surface electromyography (sEMG) for assistive robotics. Her most cited work, "Real-time modeling and feature extraction method of surface electromyography signal for hand movement classification based on oscillatory theory" (2022, 7 citations), introduces a groundbreaking point-to-point signal analysis approach that departs from traditional segmentation methods. This innovation enables more precise, real-time classification of hand movements, directly advancing the control of prosthetic limbs and exoskeleton robots. Dr. Mu’s contributions address a critical bottleneck in human motion intention recognition, offering a theoretical framework that bridges oscillatory dynamics with practical feature extraction. Her work has been cited in studies spanning rehabilitation engineering and neural interfaces, underscoring its impact on both fundamental research and applied technology. By improving the responsiveness and accuracy of myoelectric control systems, Dr. Mu is helping to create more intuitive, adaptive assistive devices—a vital step toward restoring natural movement for individuals with limb loss or motor impairments.
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