Papers
4
Total Citations
24
H-Index
2
About
Lili Pei is a pioneering researcher in brain-computer interfaces (BCI), with a focused expertise in decoding motor imagery and movement parameters from electroencephalography (EEG) signals. Her work centers on understanding how the brain encodes speed and limb-specific commands during imagined and actual movements, a critical step toward developing intuitive brain-controlled robotic interfaces (BCRI). Pei’s major contributions include the systematic investigation of time-domain features and event-related spectral perturbations during periodic motor imagery at different speeds (e.g., 2 Hz vs. 4 Hz). She demonstrated that slow cortical potentials and phase-locked oscillations carry discriminative information about imagined movement speed and limb (left/right finger, toe). Her most-cited paper (11 citations) established foundational relationships between speed and slow potentials, while subsequent work (9 citations) explored spectral power perturbations across six motor imagery tasks. Pei also advanced offline classification of imagined speeds, showing that reactive rhythm activities can distinguish between fast and slow finger movements. Her research, though early-stage with small subject cohorts, provides essential groundwork for non-invasive BCI systems that require nuanced, speed-aware motor control.
Research Focus
Key Achievements
Top Papers
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