A quick approach to detect epilepsy and seizure in brain Online publication date: Mon, 07-Nov-2016
by S. Aarthishree; M. Jayashree; J. Rhinose Fathima
International Journal of Advanced Intelligence Paradigms (IJAIP), Vol. 8, No. 4, 2016
Abstract: Brain, one of the essential organs in humans is likely to be affected by degenerative disorder, known as epilepsy. Epileptic seizure is caused by deviations in electrical activity of certain brain cells. Usual diagnostic tests are EEGs and brain scans, which are cost effective. Here, the electroencephalogram signal plays a major part in diagnosing epilepsy. But the detection needs the analysis of whole EEG with respect to time. Here, the ultimate aim is to make the process more accurate and fast in detection by limiting the number of data points through setting threshold limits. It allows reduction in data points to obtain denoised signal. Process flow: EEG signal is denoised by performing the integration process of wavelet transform and Otsu threshold process. By applying the inverse wavelet transform original signal get obtained. Then by sample entropy their feature gets extracted and is used along with extreme learning machine model.
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