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The difference of EEG complexity between normal and melancholic subjects is analyzed, which tries to reveal the characteristics of melancholic's EEG complexity. In this paper, 16-channel EEG data are recorded in 10 melancholic and 10 healthy persons under two states: a resting condition with eyes closed, a mental arithmetic with eyes closed. And then the… (More)
The high order pattern discovery algorithm is applied to classify schizophrenia and health's EEG signals. Samples of 780 schizophrenia and health EEG pieces are classified. The result shows that the classification accuracy can achieve 90% in 6-order. The 6-orders are associated with frontal polar, temporal and occipital regions.
Objective: To realize the automatic classification between melancholic and healthy persons by extracting the disease features from the melancholic's EEG signals. Methods: 1. Extracting the features from the EEG signals of melancholic and healthy persons; 2. Obtaining the characteristic parameters such as the maximum, minimum, mean and standard deviation of… (More)