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

Authors

  • Goregaonkar MB Dept. of Electronics and Telecommunication Eng. Dr. Babasaheb. Ambedkar Technological University, Lonere, Maharashtra, India

DOI:

https://doi.org/10.26438/ijcse/v7i6.554558

Keywords:

EEG, DWT, NN

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.

References

[1]. J.Sateesh and P Bhuvaneswari, “Analysis of EEG signals and its categorization” (ICMOC 2012)

[2]. S.A Taywade and Dr. R. D.Raut, “EEG signal analysis with different methodologies”, NCIPET 2014

[3]. Sachin Garg and Rakesh Narvey,” Denoising and feature extraction of EEG signal using wavelet transform. IJES

[4]. Mohd Syakir Fathillah, Rosmina Jaafar , Kalaivani Chellappan ,Rabani Remli, “A Study on EEG signals of eye open and eye closed using Discrete wavelet transform”, IECBES 2016.

[5]. En.wikipedia.org, ‘Daubechies wavelet’

[6]. Z H Khan, Nasir Hussain, Mohsin I. Tiwana, Classification of EEG signals for wrist and grip movements using ESN, BIOMEDICAL

[7]. RESEARCH 2017; 28(3): 1095- 1102, ISSN 0970-938X

[8]. 7)Fatemeh Shahlei, Sajad Banakar, Hadi Salempoor, Mahmood Aflaki,Seyed Mohammad Sadegh, Barghi Keyvan, “ Feature classification of EEG signal using signal energy in MRA and RBF for detecting seizure and epilepsy.2017.

[9]. Sayali M Wani, Sukant Sabut, S.L.Nalbalwar “Detection of epileptic seizure using wavelet transform and neural network classifier”, ICCASP 2018.

[10]. Soumya Sen Gupta and Sumeet Agarwal, “Classification and analysis of EEG signals for imagined motor movements”.

Downloads

Published

2019-06-30
CITATION
DOI: 10.26438/ijcse/v7i6.554558
Published: 2019-06-30

How to Cite

[1]
M. B. Goregaonkar, “A Classification of EEG Signals Of Eye-Open and Eye-Closed Using Neural Network”, Int. J. Comp. Sci. Eng., vol. 7, no. 6, pp. 554–558, Jun. 2019.

Issue

Vol. 7 No. 6 (2019): IJCSE June Edition

Section

Research Article

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.