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A Classification of EEG Signals Of Eye-Open and Eye-Closed Using Neural Network

Mrinmai Bhalchandra Goregaonkar1

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-6 , Page no. 554-558, Jun-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i6.554558

Online published on Jun 30, 2019

Copyright © Mrinmai Bhalchandra Goregaonkar . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Mrinmai Bhalchandra Goregaonkar, “A Classification of EEG Signals Of Eye-Open and Eye-Closed Using Neural Network,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.554-558, 2019.

MLA Style Citation: Mrinmai Bhalchandra Goregaonkar "A Classification of EEG Signals Of Eye-Open and Eye-Closed Using Neural Network." International Journal of Computer Sciences and Engineering 7.6 (2019): 554-558.

APA Style Citation: Mrinmai Bhalchandra Goregaonkar, (2019). A Classification of EEG Signals Of Eye-Open and Eye-Closed Using Neural Network. International Journal of Computer Sciences and Engineering, 7(6), 554-558.

BibTex Style Citation:
@article{Goregaonkar_2019,
author = { Mrinmai Bhalchandra Goregaonkar},
title = {A Classification of EEG Signals Of Eye-Open and Eye-Closed Using Neural Network},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2019},
volume = {7},
Issue = {6},
month = {6},
year = {2019},
issn = {2347-2693},
pages = {554-558},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4590},
doi = {https://doi.org/10.26438/ijcse/v7i6.554558}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i6.554558}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4590
TI - A Classification of EEG Signals Of Eye-Open and Eye-Closed Using Neural Network
T2 - International Journal of Computer Sciences and Engineering
AU - Mrinmai Bhalchandra Goregaonkar
PY - 2019
DA - 2019/06/30
PB - IJCSE, Indore, INDIA
SP - 554-558
IS - 6
VL - 7
SN - 2347-2693
ER -

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Abstract

EEG (electroencephalography) is a famous modality to study the appearance of electrical activity over the scalp. This paper includes an experiment which gives 90% accuracy of recorded signals. In this experiment, classification is done in the open eye or closed eye. These signals are decomposed by using DWT into the sub-band frequencies. Then features are extracted from these frequencies. By these features, the classification will carry out by using the ANN classifier. Classification accuracy is a useful content that gives the reliability to perform the imagined movements.

Key-Words / Index Term

EEG, DWT, NN

References

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