UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 9 Issue 10
October-2022
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2210390


Registration ID:
503772

Page Number

d622-d628

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Title

EEG SIGNAL ANALYSIS FOR EPILEPSY DISEASE USING MACHINE LEARNING TECHNIQUES

Abstract

Epilepsy is recognized to be one among the most critical and central nervous system (neurological) disorder affecting the human brain. Epilepsy can be detected with the help of Electroencephalography (EEG), EEG is an effective technique which is used to monitor the brain activity. EEG also used for diagnosing epilepsy. By analyzing the EEG raw data epilepsy can be detected at early stages. In this paper, we presented a technique for detecting the disease using EEG raw data. The proposed model is made using a neural network technique called artificial neural network (ANN).The model will be trained using the larger dataset of patient diseases. Finally, the model will be tested against random samples to obtain the results. The results obtained 92.6% of maximum accuracy using ANN.

Key Words

Epilepsy, Electroencephalography, Artificial Neural Network, Machine Learning Signal Analysis, Medical Applications.

Cite This Article

"EEG SIGNAL ANALYSIS FOR EPILEPSY DISEASE USING MACHINE LEARNING TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 10, page no.d622-d628, October-2022, Available :http://www.jetir.org/papers/JETIR2210390.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"EEG SIGNAL ANALYSIS FOR EPILEPSY DISEASE USING MACHINE LEARNING TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 10, page no. ppd622-d628, October-2022, Available at : http://www.jetir.org/papers/JETIR2210390.pdf

Publication Details

Published Paper ID: JETIR2210390
Registration ID: 503772
Published In: Volume 9 | Issue 10 | Year October-2022
DOI (Digital Object Identifier):
Page No: d622-d628
Country: Srikakulam, Andhra Pradesh, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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