Feature selection for EEG-based discrimination between imagination of left and right hand movements

• Autorzy: Binias B. , Palus H.
• Języki publikacji: EN

Abstrakty

EN

: In this article was analyzed an influence of selected features on the accuracy of discrimination between imagination of right and left hand movements based on recorded EEG waveforms. The study showed a significant advantage that individual selection of features and a classification algorithm for analyzed data holds over the more general approach. The results were compared with the results obtained by the participants of the "BCI competition IV" and placed in the top three.

Słowa kluczowe

EN

EEG signal; brain-computer interfaces; feature extraction; classification; lateralized brain activity

• Wydawca: Wydawnictwo PAK
• Czasopismo: Measurement Automation Monitoring
• Rocznik: 2015
• Tom: Vol. 61, No. 4
• Strony: 94--97
• Opis fizyczny: Bibliogr. 8 poz., rys., tab., wzory

Twórcy

autor

Binias B.

• Institute of Automatic Control, Silesian University of Technology

autor

Palus H.

• Institute of Automatic Control, Silesian University of Technology

Bibliografia

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• [2] Pfurtscheller G., Lopes da Silva F. H.: Event-related EEG/MEG synchronization and desynchronization: basic principles. Clinical Neurophysiology, vol. 110, pp. 1842-1857, 1999.
• [3] Yuan Yang, Chevallier S., Wiart J., Bloch I.: Time-frequency optimization for discrimination between imagination of right and left hand movements based on two bipolar electroencephalography channels, EURASIP Journal on Advances in Signal Processing, vol. 38, pp. 1-18, 2014.
• [4] Lotte F., Congedo M., Lécuyer A., Lamarche F., Arnaldi B.: A review of classification algorithms for EEG-based brain–computer interfaces, Journal of Neural Engineering, vol. 4, R1-R13, 2007.
• [5] Tangermann M., Müller K. R., Aertsen A., Birbaumer N., Braun C., Brunner C., Leeb R., Mehring C., Miller K. J., Müller-Putz G. R., Nolte G., Pfurtscheller G., Preissl H., Schalk G., Schlögl A., Vidaurre C., Waldert S., Blankertz B.: Review of the BCI competition IV, Frontiers in Neuroscience vol. 6, pp. 1-31, 2012.
• [6] Schlögl A., Kronegg J., Huggins J. E., Mason S. G.: Evaluation criteria in BCI research. Toward brain-computer interfacing, Dornhege G. et al., MIT Press, pp. 327–342, 2007.
• [7] Garcés Correa A., Laciar E., Patiño H. D., Valentinuzzi M. E.: Artifact removal from EEG signals using adaptive filters in cascade, Journal of Physics: Conference Series, vol. 90, pp. 1-10, 2007.
• [8] Vidaurre C., Kramer N., Blankertz B., Schlogl A.: Time domain parameters as a feature for EEG-based brain–computer interfaces, Neural Networks, vol. 22, pp. 1313–1319, 2009.