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Reseach Article

Analysis of EEG Signal for the Detection of Brain Abnormalities

Published on May 2014 by M. Kalaivani, V. Kalaivani, V. Anusuya Devi
International Conference on Simulations in Computing Nexus
Foundation of Computer Science USA
ICSCN - Number 2
May 2014
Authors: M. Kalaivani, V. Kalaivani, V. Anusuya Devi
81f7a1ef-72d8-43bd-8310-8dcba4be4644

M. Kalaivani, V. Kalaivani, V. Anusuya Devi . Analysis of EEG Signal for the Detection of Brain Abnormalities. International Conference on Simulations in Computing Nexus. ICSCN, 2 (May 2014), 1-6.

@article{
author = { M. Kalaivani, V. Kalaivani, V. Anusuya Devi },
title = { Analysis of EEG Signal for the Detection of Brain Abnormalities },
journal = { International Conference on Simulations in Computing Nexus },
issue_date = { May 2014 },
volume = { ICSCN },
number = { 2 },
month = { May },
year = { 2014 },
issn = 0975-8887,
pages = { 1-6 },
numpages = 6,
url = { /proceedings/icscn/number2/16151-1011/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Simulations in Computing Nexus
%A M. Kalaivani
%A V. Kalaivani
%A V. Anusuya Devi
%T Analysis of EEG Signal for the Detection of Brain Abnormalities
%J International Conference on Simulations in Computing Nexus
%@ 0975-8887
%V ICSCN
%N 2
%P 1-6
%D 2014
%I International Journal of Computer Applications
Abstract

In the field of medical science, one of the major ongoing researches is the diagnosis of the abnormalities in brain. The Electroencephalogram (EEG) is a tool for measuring the brain activity which reflects the condition of the brain. EEG is very effective tool for understanding the complex behaviour of the brain. The aim of this study is to classify the EEG signal as normal or abnormal. It is proposed to develop an automated system for the classification of brain abnormalities. The proposed system includes pre-processing, feature extraction, feature selection and classification. In pre-processing the noises are removed. The discrete wavelet transform is used to decompose the EEG signal into sub-band signals. The feature extraction methods are used to extract the time domain and frequency domain features of the EEG signal.

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Index Terms

Computer Science
Information Sciences

Keywords

Electroencephalogram Brain Diseases Wavelet Transform Eeg Waves Feature Extraction