Development of Alzheimer Disease Classification System using FBNN

Authors

  • R. Sangeetha
  • G. Aravindh

Abstract

Alzheimer’s disease (AD) plays an important role in the medical signal processing using EEG signals. It is an irreversible neurodegenerative dementia that often occurs at the age of 70. 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 suitable diagnosis methods to improve the quality of AD 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 observed that Box counting fractal feature with 20 orders using FBNN reported the highest classification accuracy of 90 per cent and the Box counting with 5th order using FBNN reported the lowest classification accuracy of 78 per cent.

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Published

2020-04-11

Issue

Section

Articles