Face Recognition using Machine Learning Algorithms

Abstract

Epilepsy is a disorder of central nervous system (CNS) which shows the symptoms like the loss of consciousness and convulsions. In epilepsy, the electrical discharge shows abnormality that leads to uncontrolled convulsion and movement, and loss of consciousness hence it can leads to the serious injury or even death. The elderly is affected mostly by this disease. This main cause of this disease is unknown but it can treated medically. Automatic detection of seizure using computerized technique is the necessity. Hence in this approach, an automatic seizure detection system using statistical feature and machine learning classification algorithm have been presented. The system used EEG signal as an input. First the signal is processed using Chebyschev filter to remove the noise. The signal is then decomposed into five sub-bands using discrete wavelet transform. The feature were extracted from decomposed subband and finally feature are trained and text using K-Nearest Neighbor classifier. The proposed system achieved an accuracy of 85% using KNN classifier for K=1.