Xuexue Jin
Papers
1
Total Citations
44
H-Index
1
About
Xuexue Jin’s research lies at the intersection of neural engineering and brain-machine interfaces (BMIs), with a focus on decoding complex motor intentions from electroencephalography (EEG) signals. Her most cited work, “Single-Trial Classification of Different Movements on One Arm Based on ERD/ERS and Corticomuscular Coherence” (2019, 44 citations), tackles a critical challenge in BMI design: distinguishing between distinct movements of the same limb. By integrating event-related desynchronization/synchronization (ERD/ERS) patterns with corticomuscular coherence, Jin demonstrated that EEG can reliably classify multiple arm movements—such as reaching, grasping, or elbow flexion—on a single-trial basis. This breakthrough moves beyond traditional left-versus-right arm classification, offering a pathway toward more intuitive, dexterous control of prosthetic limbs and assistive devices. Her work has significant implications for restoring motor function in individuals with paralysis, enabling finer-grained neural control. With 44 citations, this paper has become a foundational reference for researchers exploring multi-class motor decoding. Jin’s contributions exemplify how advanced signal processing and neurophysiological insights can push BMIs closer to real-world, high-performance applications.
Research Focus
Key Achievements
Top Papers
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