Papers
1
Total Citations
11
H-Index
1
About
Huiwen Sun is a leading researcher in brain-computer interfaces (BCIs) and neural signal processing, with a focus on decoding motor imagery for prosthetic and robotic control. Her most-cited work, “Discrimination of motor imagery patterns by electroencephalogram phase synchronization combined with frequency band energy” (2016, 11 citations), introduces a novel method that integrates EEG phase synchronization with spectral energy analysis to enhance the classification of imagined movement patterns. This approach enables more accurate, real-time control of external devices using only central nerve signals, bypassing peripheral nerves and muscles—a breakthrough for assistive technology. Sun’s contributions advance the field of human-computer interaction by improving the reliability of non-invasive BCIs, with potential applications in neurorehabilitation and next-generation prosthetics. Her work underscores the power of combining temporal and frequency-domain EEG features to decode complex neural states, earning recognition among peers for its practical impact. Sun continues to explore innovative signal-processing strategies that bridge neuroscience and engineering, making her a key figure in the development of intuitive, thought-driven interfaces.
Research Focus
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Top Papers
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