Classification of Epileptic EEG Signals by Wavelet based CFC

Authors: Amirmasoud Ahmadi, Mahsa Behroozi, Vahid Shalchyan, Mohammad Reza Daliri
Published: 2018-05-04

Source: https://arxiv.org/abs/1805.01743

PDF: https://arxiv.org/pdf/1805.01743

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透かし技術の堅牢性 時間系列分析 性能評価指標

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Abstract

Electroencephalogram, an influential equipment for analyzing humans activities and recognition of seizure attacks can play a crucial role in designing accurate systems which can distinguish ictal seizures from regular brain alertness, since it is the first step towards accomplishing a high accuracy computer aided diagnosis system (CAD). In this article a novel approach for classification of ictal signals with wavelet based cross frequency coupling (CFC) is suggested. After extracting features by wavelet based CFC, optimal features have been selected by t-test and quadratic discriminant analysis (QDA) have completed the Classification.