A Comprehensive Analysis of Alcoholic EEG Signals with Detrend Fluctuation Analysis and Post Classifiers

Sunil Kumar Prabhakar, Harikumar Rajaguru, Seong Whan Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Different pathological and physiological activities of the brain can be analyzed by means of utilizing Electroencephalography (EEG) signals. One such important activity which can be assessed and understood with the help of electrical representation of the brain signals is alcoholism. Alcoholism is a serious concern to many in the world as it affects the vital organs of the human body like liver, brain, lungs, heart, blood, immunity levels etc. In the arena of biomedical research, classification of alcoholic subjects from EEG signals is quite a challenging task. In this paper, the alcoholic EEG signals are analyzed comprehensively for a single alcoholic patient and it is classified with many post classifiers. Initially Correlation Dimension features are extracted from the EEG signals and then it is classified with the help of Detrend Fluctuation Analysis (DFA). In order to improve the classification accuracy further, it is again classified with 6 other post classifiers such as Linear Discriminant Analysis (LDA), Kernel LDA, Firefly algorithm, Gaussian Mixture Model (GMM), Logistic Regression (LR) and Softmax Discriminant Classifier (SDC). Results report a high classification accuracy of 97.91% when GMM is employed followed by a classification accuracy of 97.33% when Logistic Regression is employed. A comparatively low classification accuracy of 89.6% is obtained when LDA was employed.

Original languageEnglish
Title of host publication7th International Winter Conference on Brain-Computer Interface, BCI 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538681169
DOIs
Publication statusPublished - 2019 Feb 1
Event7th International Winter Conference on Brain-Computer Interface, BCI 2019 - Gangwon, Korea, Republic of
Duration: 2019 Feb 182019 Feb 20

Publication series

Name7th International Winter Conference on Brain-Computer Interface, BCI 2019

Conference

Conference7th International Winter Conference on Brain-Computer Interface, BCI 2019
CountryKorea, Republic of
CityGangwon
Period19/2/1819/2/20

Keywords

  • Alcoholism
  • DFA
  • EEG
  • GMM
  • LDA

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Signal Processing
  • Neuroscience (miscellaneous)

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  • Cite this

    Prabhakar, S. K., Rajaguru, H., & Lee, S. W. (2019). A Comprehensive Analysis of Alcoholic EEG Signals with Detrend Fluctuation Analysis and Post Classifiers. In 7th International Winter Conference on Brain-Computer Interface, BCI 2019 [8737328] (7th International Winter Conference on Brain-Computer Interface, BCI 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IWW-BCI.2019.8737328