Data set I
Department of Biomedical Engineering
Hangzhou, 310027, P. R. China
Counselor: Tong Qinye. Zhang Hong. Huang Hai
Feature: Data from every electrode was transformed to time-frequency domain by Hilbert-Huang Transform. Extract Standard deviation of every time-frequency window as feature.
Classification method: mahalanobis distance to class center.
Hilbert-Huang Transform of ECoG from all electrodes.
Extract Standard deviation of every time-frequency window (5Hz*0.2S) as feature.
Calculated error rate by leave-one-out use train data. Select 7 electrodes (29,30,31,38,39,40,46) that has lowest error rate with single time-frequency window.
Use Standard deviation of time-frequency domain from all 7 electrodes, single frequency band and 11 continuous time windows as feature. Calculated class center of class 1 and calss-1 from train data.
Use mahalanobis distance to classify the test data.
Format: matlab format(matlab 6.1)