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A Comparison of EEG Processing Methods to Improve the Performance of BCI

Arjon Turnip, Demi Soetraprawata, and Dwi E. Kusumandari
Technical Implementation Unit for Instrumentation Development Indonesian Institute of Sciences, Bandung, Indonesia
Abstract—Electroencephalogram (EEG) recordings providean important means of brain-computer communication, buttheir classification accuracy is limited by unforeseeablesignal variations due to artifacts or recognizer-subjectfeedback. In this paper, we propose a comparison ofprocessing method (i.e., NPCA, JADE, and SOBI) entailingtime-series EEG signals. Finally, the promising resultsreported here (up to 94% average classification accuracyand 36.4% improvement of maximum average transfer rate)reflect the considerable potential of EEG for the continuousclassification of mental states.

Index Terms—brain computer interface (BCI), classificationaccuracy, transfer rate, NPCA, JADE, SOBI,electroencephalogram (EEG)

Cite: Arjon Turnip, Demi Soetraprawata, and Dwi E. Kusumandari, "A Comparison of EEG Processing Methods to Improve the Performance of BCI," International Journal of Signal Processing Systems,  Vol. 1, No. 1, pp. 63-67,  June 2013.doi: 10.12720/ijsps.1.1.63-67
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