Feature extraction and classification study with energy entropy of IMFs to different mental tasks in EEG
Miao Ma · Computer Engineering and Applications Journal · 2009
A new feature extraction and selection method based on the energy entropy of Intrinsic Mode Functions (IMFs) is presented.Three types of different mental tasks in EEG signals radiated from the targets are decomposed into their respective IMFs using the Empirical Mode Decomposition (EMD) procedure,and the energies of the same IMF of three types of signals are different.The energy entropies of the IMFs are calculated.K-neighbor classifier is used for classification experiments for three types of signals.The results show that the correct identification ratio of experiments above 75%.