Peirang Li
Papers
3
Total Citations
15
H-Index
2
About
Peirang Li is a researcher at the forefront of brain–machine interfaces (BMIs) and assistive robotics, with a focused expertise in EEG-based control for upper-limb power augmentation. Li’s major contributions lie in decoding voluntary shoulder movements—specifically flexion and extension—from electroencephalography (EEG) signals to drive exoskeleton systems that enhance human strength. Their 2020 study on EEG-based EMG estimation of the shoulder joint (10 citations) established a foundational method for translating neural activity into mechanical assistance, directly addressing the challenge of intuitive, non-invasive control for both rehabilitation and healthy individuals. Li further refined feature extraction techniques for shoulder movement classification (2018, 3 citations) and pioneered neurofeedback training protocols (2021, 2 citations) to help users reliably modulate their own brain rhythms for more effective BMI operation. This work bridges the gap between neural signal processing and practical wearable robotics, offering a scalable path toward augmenting human physical capability. Li’s research is particularly notable for its dual focus on clinical rehabilitation and performance enhancement, making it relevant to engineers, neuroscientists, and clinicians alike.
Research Focus
Key Achievements
Top Papers
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