Med Biol Eng Comput - Evaluation of feature extraction methods for EEG-based brain-computer interfaces in terms of robustness to slight changes in electrode locations.

Tópicos

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Resumo

To date, most EEG-based brain-computer interface (BCI) studies have focused only on enhancing BCI performance in such areas as classification accuracy and information transfer rate. In practice, however, test-retest reliability of the developed BCI systems must also be considered for use in long-term, daily life applications. One factor that can affect the reliability of BCI systems is the slight displacement of EEG electrode locations that often occurs due to the removal and reattachment of recording electrodes. The aim of this study was to evaluate and compare various feature extraction methods for motor-imagery-based BCI in terms of robustness to slight changes in electrode locations. To this end, EEG signals were recorded from three reference electrodes (Fz, C3, and C4) and from six additional electrodes located close to the reference electrodes with a 1-cm inter-electrode distance. Eight healthy participants underwent 180 trials of left- and right-hand motor imagery tasks. The performance of four different feature extraction methods [power spectral density (PSD), phase locking value (PLV), a combination of PSD and PLV, and cross-correlation (CC)] were evaluated using five-fold cross-validation and linear discriminant analysis, in terms of robustness to electrode location changes as well as regarding absolute classification accuracy. The quantitative evaluation results demonstrated that the use of either PSD- or CC-based features led to higher classification accuracy than the use of PLV-based features, while PSD-based features showed much higher sensitivity to changes in EEG electrode location than CC- or PLV-based features. Our results suggest that CC can be used as a promising feature extraction method in motor-imagery-based BCI studies, since it provides high classification accuracy along with being little affected by slight changes in the EEG electrode locations.

Resumo Limpo

date eegbas braincomput interfac bci studi focus enhanc bci perform area classif accuraci inform transfer rate practic howev testretest reliabl develop bci system must also consid use longterm daili life applic one factor can affect reliabl bci system slight displac eeg electrod locat often occur due remov reattach record electrod aim studi evalu compar various featur extract method motorimagerybas bci term robust slight chang electrod locat end eeg signal record three refer electrod fz c c six addit electrod locat close refer electrod cm interelectrod distanc eight healthi particip underw trial left righthand motor imageri task perform four differ featur extract method power spectral densiti psd phase lock valu plv combin psd plv crosscorrel cc evalu use fivefold crossvalid linear discrimin analysi term robust electrod locat chang well regard absolut classif accuraci quantit evalu result demonstr use either psd ccbase featur led higher classif accuraci use plvbase featur psdbase featur show much higher sensit chang eeg electrod locat cc plvbase featur result suggest cc can use promis featur extract method motorimagerybas bci studi sinc provid high classif accuraci along littl affect slight chang eeg electrod locat

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