Reduced Burden of Individual Calibration Process in Brain-Computer Interface by Clustering the Subjects based on Brain Activation

• Published in: Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics pp. 2139 - 2143
• Main Authors: Kim, Young-Tak, Lee, Seho, Kim, Hakseung, Lee, Seung-Bo, Lee, Seong-Whan, Kim, Dong-Joo
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.10.2019
• Subjects: Conferences; Cybernetics

Electroencephalography (EEG) is the primary modality for estimating the user intention in brain-computer interface (BCI). However, the suppression of the inter-subject variability (ISV) remains as a major challenge in constructing a reliable EEG-based BCI model. Subject-specific classification model...