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Updated: Sep 1, 2025

Assessment and Communication for People with Disorders of Consciousness
Published on: August 1, 2017
Hojong Choi1, Junghun Park2, Yeon-Mo Yang2
1Department of Electronic Engineering, Gachon University, 1342 Seongnam-daero, Seongnam 13306, Korea.
A new Quick-Response Eigenface Analysis (QR-EFA) method enhances brain-computer interface (BCI) accuracy for motor imagery (MI) tasks. This approach significantly improves classification performance on standard BCI datasets.
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