EEG-Based Systematic Explainable Alzheimer’s Disease and Mild Cognitive Impairment Identification Using Novel Rational Dyadic Biorthogonal Wavelet Filter Banks-Reference-Cited by-同舟云学术

EEG-Based Systematic Explainable Alzheimer’s Disease and Mild Cognitive Impairment Identification Using Novel Rational Dyadic Biorthogonal Wavelet Filter Banks

Published:2023-11-08 Issue: Volume: Page:
ISSN:0278-081X
Container-title:Circuits, Systems, and Signal Processing
language:en
Short-container-title:Circuits Syst Signal Process

Author:

Puri Digambar V.^ORCID,Nalbalwar Sanjay L.,Ingle Pallavi P.

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Signal Processing

Link

https://link.springer.com/content/pdf/10.1007/s00034-023-02540-x.pdf

Reference55 articles.

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3. D. Abasolo, R. Hornero, J. Escudero, C. Gomez, M. Garcia, M. Lopez, Approximate entropy and mutual information analysis of the electroencephalogram in alzheimer’s disease patients, In: IET 3rd International Conference on Advances in Medical, Signal, and Information Processing-MEDSIP, pp. 1–4 (2006)

4. A. Acharyya, P. Jadhav, V. Bono, K. Maharatna, G. Naik, Low-complexity hardware design methodology for reliable and automatedremoval of ocular and muscular artifact from EEG. Comput. Methods Programs Biomed. 158, 123–133 (2018). https://doi.org/10.1016/j.cmpb.2018.02.009

5. A. Al-Ani, I. Koprinska, G. Naik, R. Khushaba, A dynamic channel selection algorithm for the classification of EEG and EMG data. In: International Joint Conference on Neural Networks (IJCNN), pp. 4076–4081 (2016). https://doi.org/10.1109/IJCNN.2016.7727730

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