skip to main content
Language:
Search Limited to: Search Limited to: Resource type Show Results with: Show Results with: Search type Index

Feature Selection Methods Comparison for EEG-based Classifier Constructed Using Discrete Wavelet Transform Features

Journal of physics. Conference series, 2022-07, Vol.2291 (1), p.12003 [Peer Reviewed Journal]

Published under licence by IOP Publishing Ltd ;Published under licence by IOP Publishing Ltd. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1742-6588 ;EISSN: 1742-6596 ;DOI: 10.1088/1742-6596/2291/1/012003

Full text available

Citations Cited by
  • Title:
    Feature Selection Methods Comparison for EEG-based Classifier Constructed Using Discrete Wavelet Transform Features
  • Author: Tsybenov, B ; Svetlakov, M ; Hodashinsky, I
  • Subjects: Classifiers ; Discrete Wavelet Transform ; Electroencephalography
  • Is Part Of: Journal of physics. Conference series, 2022-07, Vol.2291 (1), p.12003
  • Description: Abstract The paper presents the results of a study in the application of electroencephalography (EEG) for user authentication using discrete wavelet transform. The Leipzig Study for Mind-Body-Emotion Interactions dataset (LEMON) was used. Mean value, standard deviation, and root mean square value are used as features. Feature selection methods based on correlation, on mutual information, and on the χ2 criterion are used for reduce feature space. The SVM model is used for classification. The efficiency of constructed classifier has been tested using cross-validation procedure. Classifier built on feature reduced data via mutual information criteria have improved accuracy (97.4%) with feature space nearly halved (183 features) compared to baseline classifier.
  • Publisher: Bristol: IOP Publishing
  • Language: English
  • Identifier: ISSN: 1742-6588
    EISSN: 1742-6596
    DOI: 10.1088/1742-6596/2291/1/012003
  • Source: Geneva Foundation Free Medical Journals at publisher websites
    IOPscience (Open Access)
    Institute of Physics Open Access Journal Titles
    ProQuest Central
Back to results list
INSPIRE LIBRARY - TON DUC THANG UNIVERSITY (84-028) 37 755 057 Feedback
19 Nguyen Huu Tho St. Dist.7, HCM thuvien@tdtu.edu.vn

Copyright © 2017 INSPIRE LIBRARY - TON DUC THANG UNIVERSITY

Searching Remote Databases, Please Wait