Detection of fast and slow hand movements from motor imagery EEG signals

Saugat Bhattacharyya, Munshi Asif Hossain, Amit Konar, D. N. Tibarewala, Janarthanan Ramadoss

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

3 Citations (Scopus)
3 Downloads (Pure)

Abstract

Classification of Electroencephalography (EEG) signal is an open area of re-search in Brain-computer interfacing (BCI). The classifiers detect the different mental states generated by a subject to control an external prosthesis. In this study, we aim to differentiate fast and slow execution of left or right hand move-ment using EEG signals. To detect the different mental states pertaining to motor movements, we aim to identify the event related desynchronization/synchronization (ERD/ERS) waveform from the incoming EEG signals. For this purpose, we have used Welch based power spectral density estimates to create the feature vector and tested it on multiple support vector machines, Nave Bayesian, Linear Discriminant Analysis and k-Nearest Neighbor classifiers. The classification accuracies produced by each of the classifiers are more than 75% with naïve Bayesian yielding the best result of 97.1%.

Original languageEnglish
Title of host publicationAdvanced Computing, Networking and Informatics - Proceedings of the Second International Conference on Advanced Computing, Networking and Informatics, ICACNI 2014
Pages645-652
Number of pages8
EditionVOL 1
DOIs
Publication statusPublished - 1 Jan 2014
Event2nd International Conference on Advanced Computing, Networking and Informatics, ICACNI 2014 - Kolkata, India
Duration: 24 Jun 201426 Jun 2014

Publication series

NameSmart Innovation, Systems and Technologies
NumberVOL 1
Volume27
ISSN (Print)2190-3018
ISSN (Electronic)2190-3026

Conference

Conference2nd International Conference on Advanced Computing, Networking and Informatics, ICACNI 2014
CountryIndia
CityKolkata
Period24/06/1426/06/14

Keywords

  • Brain-computer interfacing
  • Electroencephalography
  • Event related desynchronization/synchronization
  • Motor imagery
  • Pattern classifiers

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  • Cite this

    Bhattacharyya, S., Hossain, M. A., Konar, A., Tibarewala, D. N., & Ramadoss, J. (2014). Detection of fast and slow hand movements from motor imagery EEG signals. In Advanced Computing, Networking and Informatics - Proceedings of the Second International Conference on Advanced Computing, Networking and Informatics, ICACNI 2014 (VOL 1 ed., pp. 645-652). (Smart Innovation, Systems and Technologies; Vol. 27, No. VOL 1). https://doi.org/10.1007/978-3-319-07353-8_74