Abstract
Brain is the most important organ of the human body. It controls the entire function of the human body. Early detection of brain abnormality enhances proper medication and better health. Electroencephalogram (EEG) signal is the measure of the electrical activity of the brain. This paper suggests the signal algorithm for detection of brain abnormalities migraine and seizure by using EEG signals. The dataset consists of 67 persons of EEG signals with sampling rate of 128Hz and 256Hz. The statistical features of the power spectral density of the EEG signals are used as the input for the SVM classifier for detection of seizure and migraine brain abnormalities. Recognition rate of 100% for the sampling rate of 256Hz and 89% for the sampling rate of 128Hz is achieved.
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