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RETRACTED: Electroencephalogram (EEG) signal classification for brain–computer interface using discrete wavelet transform (DWT)

U. Rajashekhar, D. Neelappa, L. Rajesh

International Journal of Intelligent Unmanned Systems

ISSN: 2049-6427

Article publication date: 9 February 2021

Issue publication date: 7 January 2022

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This article was retracted on 11 Jun 2024.

Retraction notice

The publishers of the International Journal of Intelligent Unmanned Systems wish to retract the article Rajashekhar, U., Neelappa, D. and Rajesh, L. (2022), Electroencephalogram (EEG) signal classification for brain–computer interface using discrete wavelet transform (DWT), International Journal of Intelligent Unmanned Systems, Vol. 10 No. 1, pp. 86-97. https://doi.org/10.1108/IJIUS-09-2020-0057

An internal investigation into a series of submissions has uncovered evidence that the peer review process was compromised. As a result of these concerns, the findings of the article cannot be relied upon. This decision has been taken in accordance with Emerald’s publishing ethics and the COPE guidelines on retractions.

The authors of this paper would like to note that they do not agree with the content of this notice.

The publishers of the journal sincerely apologize to the readers

Abstract

Purpose

This work proposes classification of two-class motor imagery electroencephalogram signals using different automated machine learning algorithms. Here data are decomposed into various frequency bands identified by wavelet transform and will span the range of 0–30 Hz.

Design/methodology/approach

Statistical measures will be applied to these frequency bands to identify features that will subsequently be used to train the classifiers. Further, the assessment parameters such as SNR, mean, SD and entropy are calculated to analyze the performance of the proposed work.

Findings

The experimental results show that the proposed work yields better accuracy for all classifiers when compare to state-of-the-art techniques.

Originality/value

The experimental results show that the proposed work yields better accuracy for all classifiers when compare to state-of-the-art techniques.

Keywords

Citation

Rajashekhar, U., Neelappa, D. and Rajesh, L. (2022), "RETRACTED: Electroencephalogram (EEG) signal classification for brain–computer interface using discrete wavelet transform (DWT)", International Journal of Intelligent Unmanned Systems, Vol. 10 No. 1, pp. 86-97. https://doi.org/10.1108/IJIUS-09-2020-0057

Publisher

:

Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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