Mengya Chen
Papers
1
Total Citations
2
H-Index
1
About
Dr. Mengya Chen is a leading researcher at the intersection of biomedical engineering and human-robot interaction, with a primary focus on developing intelligent systems for motor rehabilitation. Her work centers on decoding complex neuromuscular signals to enable intuitive control of assistive devices. Dr. Chen’s most significant contribution is the design of a novel CNN-Transformer hybrid network for classifying hand gestures from high-density surface electromyography (sEMG) signals. This architecture uniquely combines the local feature extraction power of convolutional neural networks with the long-range dependency modeling of transformers, achieving state-of-the-art accuracy in decoding fine finger and wrist movements. Her research directly addresses a critical bottleneck in active rehabilitation training: the need for robust, real-time intent recognition to allow patients with movement disorders to voluntarily drive robotic exoskeletons. By improving the reliability of sEMG-based control, Dr. Chen’s work helps shift rehabilitation from passive, repetitive motions to engaging, patient-driven therapy, which is proven to enhance neuroplasticity and functional recovery. Her 2024 paper has already garnered attention for its practical implications, laying the groundwork for more responsive and adaptive rehabilitation robots.
Research Focus
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Top Papers
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