Subject-specific CSP-LDA models for motor imagery EEG show significant accuracy differences across time windows and frequency bands, with an optimal average combination of 0-4 s and 4-12 Hz.
Journal of Machine Learning Research4(Dec), 1261–1269 (2003)
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Optimal Time Window and Frequency Bandwidth Parameter Combination for Subject-Specific Motor Imagery EEG Classification
Subject-specific CSP-LDA models for motor imagery EEG show significant accuracy differences across time windows and frequency bands, with an optimal average combination of 0-4 s and 4-12 Hz.