A methodology for time-frequency image processing applied to the classification of non-stationary multichannel signals using instantaneous frequency descriptors with application to newborn EEG signals

EURASIP Journal on Advances in Signal Processing

Table 6 Confusion matrices for newborn EEG classification using T-F features set {F_{S 1}, F_{S 2}, ..., F_{S 8}, F_{I 1}, ..., F_{I 5}} extracted from the TFD

The results, for each TFD, are given using the multi-class SVM classifier with newborn EEG database organized in two classes N, and S. The result between parentheses is the classification result using only the signal-related features {F_{S 1}, F_{S 2}, ..., F_{S 8}}. Sensitivity and specificity for each particular class as well as its total accuracy are also given.