Classification of Alzheimer Disease using EEG signal

Abstract

Alzheimer’s disease (AD) plays an important role in the medical image processing. It is an irreversible neurodegenerative dementia that often occurs at the age of 65. It is a kind of memory loss that related with thinking and behavior of people’s day to day lives. Therefore, the researchers are taking more efforts to find proper treatment and improve the quality of patient’s life. This paper totally organize 161 subjects of which 79 subjects EEG signals with AD and 82 subjects EEG signals with cognitive normal are analyzed  with 1 K Hz and 2 K Hz. From the results, it can be measured that AR pole tracking with 15th order using MFNN reported the highest classification accuracy of 96.5 per cent with specificity 96%, sensitivity 93% and F measure 90%.