A NEW PARAMETRIC FEATURE DESCRIPTOR FOR THE CLASSIFICATION OF EPILEPTIC AND CONTROL EEG RECORDS IN PEDIATRIC POPULATION

作者：Cabrerizo Mercedes^*; Ayala Melvin; Goryawala Mohammed; Jayakar Prasanna; Adjouadi Malek

来源：International Journal of Neural Systems, 2012, 22(2): 1250001.

DOI：10.1142/S0129065712500013

• EEG data
• temporal and frequency parameters
• artificial neural networks
• support vector machines
• EEG classification
• epileptic versus control EEG

This study evaluates the sensitivity, specificity and accuracy in associating scalp EEG to either control or epileptic patients by means of artificial neural networks (ANNs) and support vector machines (SVMs). A confluence of frequency and temporal parameters are extracted from the EEG to serve as input features to well-configured ANN and SVM networks. Through these classification results, we thus can infer the occurrence of high-risk (epileptic) as well as low risk (control) patients for potential follow up procedures.

• 出版日期2012-4