Focal and Non-Focal EEG Signal Classification by Computing Area of 2D-PSR Obtained for IMF
DOI:
https://doi.org/10.13052/jicts2245-800X.523Keywords:
Focal and Non-Focal EEG signal, Empirical mode decomposition (EMD), Intrinsic mode function (IMF), 2D-PSR (phase space representation)Abstract
The Electroencephalogram (EEG) signals are typically used indicators for the detection of epileptic seizures in the human brain by placing sensors in the scalp of the brain. In this paper, we classify focal (F) and non-focal (NF) EEG signals by computing the area of 2D-PSR obtained for intrinsic mode functions (IMFs). IMFs are obtained by disintegrating the EEG signals using Empirical mode decomposition (EMD). The main objective of this work is to classify the focal and non-focal EEG signal for the medical purpose. The proposed technique namely area of 2D-PSR method has provided promising class accuracy for classification of focal and non-focal EEG signals which gives 98.95% accuracy with polynomial and RBF kernal.
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