Papers
2
Total Citations
33
H-Index
2
About
Hanjie Deng is a leading researcher in neurorehabilitation and human-robot interaction, with a focus on decoding neural signals for assistive technologies. Their work centers on muscle synergy analysis and myoelectric control, aiming to restore motor function in individuals with neurological impairments. Deng’s highly cited 2020 study, with 22 citations, demonstrated that forearm muscle synergies remain stable across varying force levels and arm positions—a critical insight for designing robust, patient-specific neurorehabilitation protocols. This foundational research challenges assumptions about neural adaptability, offering a blueprint for more effective prosthetic and rehabilitation devices. In their 2023 work, cited 11 times, Deng introduced a novel human-robot co-adaptation framework that integrates biofeedback to continuously refine user intent recognition. This breakthrough addresses a key hurdle in myoelectric control: maintaining accuracy amid signal variability. By bridging human adaptation with machine learning, Deng’s framework enhances the reliability of neural prosthetics and rehabilitation robots. Their contributions have significant implications for personalized medicine, enabling more intuitive and responsive assistive technologies. Deng’s research is pivotal for students and engineers developing next-generation neurorehabilitation tools, blending biomechanics, signal processing, and robotics to improve quality of life for individuals with motor disabilities.
Research Focus
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Top Papers
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