Title Of Paper:
 
 
EEG Classification Using Different Feature Extraction Techniques for Emotion Recognition
Author's Name :  AbdolNabi Ansari-Asl
KeyWords:   Classification, Feature Extraction, BCI, EEG, Emotion, RBF
Pages:  49 -54
Volume: 3
Issue: 1
Year: 2015
Abstract:
 

 

Brain Computer Interface (BCI) is becoming increasingly popular. Our paper focused on an applied of it that is called recognizing emotion from human brain activity, measured by EEG signals. EEG signals were analyzed and classified into three emotions—happiness, sadness and normal. For emotion recognition, Radial Based Function (RBF) is applied to classify the emotional signals and feature extraction techniques are investigated. Using gathered data under EEG signals emotion stimulation experiments, the classifier is trained and tested. After applying classification and different feature extraction methods to 300 EEG time series, we concluded that frequency-band energy features outperformed other methods in the emotion assessment.

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