Epilepsy Detection Using Clustering Techniques

Signal processing has varied range of applications from our daily life signal processing is involved. From the communication, artificial intelligence, advance robotics to the advance bio medical applications like ECG, EEG processing etc. In this paper we have studied. EEG signal as a part of signal processing for diagnostic understanding of epilepsy. Epilepsy is one of the most common neurological with a widespread0.60.8%[1-2] of the India’s population. Two-third of the patients achieves sufficient seizure control from medicine and some other 8-10% benefit from respective surgery. For the remaining 25% of patient no sufficient treatment is currently available [3-7].Here we are proposing fixed cluster size for epilepsy feature extraction and explaining the concepts of the classification of EEG. The experiment result showed that algorithm can produce a better classification rate than the previous reported method. In last decade LS-SVM were applied to the extracted features to classify EEG signals that were proposed by Siluly [8].