Extraction and Evaluation of EEG Covariates and Their Influence on GLM Model-Reference-Cited by-同舟云学术

Extraction and Evaluation of EEG Covariates and Their Influence on GLM Model

Published:2021-08-13 Issue: Volume: Page:
ISSN:
Container-title:2021 International Symposium on Biomedical Engineering and Computational Biology
language:
Short-container-title:

Author:

Piorecka Vaclava¹,Cerny Filip¹,Piorecky Marek¹,Koudelka Vlastimil²,Horacek Jiri³,Buskova Jitka³,Brunovsky Martin³,Koprivova Jana³

Affiliation:

1. Department of Biomedical Technology,Faculty of Biomedical Engineering, CTU in Prague, Czech Republic and National Institute of Mental Health, Czech Republic

2. National Institute of Mental Health, Czech Republic

3. National Institute of Mental Health, Czech Republic and Third Faculty of Medicine, Charles University, Czech Republic

Funder

Grant Agency of the Czech Technical University in Prague

Czech Science Foundation

Czech Ministry of Education, Youth and Sports

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3502060.3502354

Reference20 articles.

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2. Subasi A and Ismail Gursoy M. EEG signal classification using PCA , ICA, LDA and support vector machines. Expert Systems with Applications. 2010 , vol. 37 , n. 12, pp. 8659 - 8666 . ISSN 09574174. DOI: 10.1016/j.eswa.2010.06.065. 10.1016/j.eswa.2010.06.065 Subasi A and Ismail Gursoy M. EEG signal classification using PCA, ICA, LDA and support vector machines. Expert Systems with Applications. 2010, vol. 37, n. 12, pp. 8659-8666. ISSN 09574174. DOI: 10.1016/j.eswa.2010.06.065.

3. A Review of Multitaper Spectral Analysis

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5. Exploring task-related variability in fMRI data using fluctuations in power spectrum of simultaneously acquired EEG