Discriminatory Features Based on Wavelet Energy for Effective Analysis of Electroencephalogram During Mental Tasks-Reference-Cited by-同舟云学术

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Discriminatory Features Based on Wavelet Energy for Effective Analysis of Electroencephalogram During Mental Tasks

Published:2022-06-03 Issue:10 Volume:41 Page:5827-5855
ISSN:0278-081X
Container-title:Circuits, Systems, and Signal Processing
language:en
Short-container-title:Circuits Syst Signal Process

Author:

Saini Manali^ORCID,Satija Udit,Upadhayay Madhur Deo

Funder

Indian Council of Medical Research

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Signal Processing

Link

https://link.springer.com/content/pdf/10.1007/s00034-022-02057-9.pdf

Reference58 articles.

1. D. Acharya et al. Comparative analysis of feature extraction technique on EEG-based dataset, in Soft Computing for Problem Solving (Springer, Singapore, 2021), pp. 405–416

2. I. Aliyu et al., Selection of optimal wavelet features for epileptic EEG signal classification with LSTM. Neural Comput. Appl. 1–21 (2021)

3. Z.A.A. Alyasseri et al., The effects of EEG feature extraction using multi-wavelet decomposition for mental tasks classification, in Proceedings of the International Conference on Information and Communication Technology (2019), pp. 139–146

4. M. Arsalidou, M.J. Taylor, Is 2+2=4? Meta-analyses of brain areas needed for numbers and calculations. Neuroimage 54, 2382–2393 (2011)

5. H. Azami, J. Escudero, Combination of signal segmentation approaches using fuzzy decision making, in 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (Milan, 2015), pp. 101–104

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