A bacterial foraging optimization and learning automata based feature selection for motor imagery EEG classification

Monalisa Pal, Saugat Bhattacharyya, Shounak Roy, Amit Konar, D. N. Tibarewala, R. Janarthanan

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

7 Citations (Scopus)
2 Downloads (Pure)

Abstract

Selection of relevant features is an open problem in Brain-computer interfacing (BCI) research. Sometimes, features extracted from brain signals are high dimensional which in turn affects the accuracy of the classifier. Selection of the most relevant features improves the performance of the classifier and reduces the computational cost of the system. In this study, we have used a combination of Bacterial Foraging Optimization and Learning Automata to determine the best subset of features from a given motor imagery electroencephalography (EEG) based BCI dataset. Here, we have employed Discrete Wavelet Transform to obtain a high dimensional feature set and classified it by Distance Likelihood Ratio Test. Our proposed feature selector produced an accuracy of 80.291% in 216 seconds.

Original languageEnglish
Title of host publication2014 International Conference on Signal Processing and Communications, SPCOM 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479946655
DOIs
Publication statusPublished - 12 Dec 2014
Event10th International Conference on Signal Processing and Communications, SPCOM 2014 - Bangalore, India
Duration: 22 Jul 201425 Jul 2014

Publication series

Name2014 International Conference on Signal Processing and Communications, SPCOM 2014

Conference

Conference10th International Conference on Signal Processing and Communications, SPCOM 2014
CountryIndia
CityBangalore
Period22/07/1425/07/14

Keywords

  • Bacterial Foraging Optimization Algorithm
  • Brain-Computer Interfacing
  • Discrete Wavelet Transform
  • Distance Likelihood Ratio Test
  • Learning Automata

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    Pal, M., Bhattacharyya, S., Roy, S., Konar, A., Tibarewala, D. N., & Janarthanan, R. (2014). A bacterial foraging optimization and learning automata based feature selection for motor imagery EEG classification. In 2014 International Conference on Signal Processing and Communications, SPCOM 2014 [6983926] (2014 International Conference on Signal Processing and Communications, SPCOM 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SPCOM.2014.6983926