Decision support systems for time-varying biomedical signals: EEG signals classification

An integrated view of the automated diagnostic systems combined with spectral analysis techniques in the classification of electroencephalogram (EEG) signals is presented. The paper includes illustrative and detailed information about implementation of automated diagnostic systems and feature extraction/selection from the EEG signals. The major objective of the paper is to be a guide for the readers, who want to develop an automated diagnostic system for classification of the EEG signals. Toward achieving this objective, this paper presents the techniques which should be considered in developing automated diagnostic systems. The author suggests that the content of the paper will assist to the people in gaining a better understanding of the techniques in the classification of the EEG signals.

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