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Biocybernetics and Biomedical Engineering

Tytuł artykułu

Spatial and spatio-temporal filtering based on common spatial patterns and Max-SNR for detection of P300 component

Autorzy Rizi, F. S.  Abootalebi, V.  Sadeghi, M. T. 
Treść / Zawartość
Warianty tytułu
Języki publikacji EN
EN Recent advances in brain-computer interfaces (BCIs) have developed a new arena for designing systems to help disabled persons to communicate with the surrounding environment. P300 speller is one of the most famous BCI systems choosing the characters from a virtual keyboard through the analysis of EEG signals. P300 detection is an important processing step of these systems. The accuracy of P300 detection highly depends on the feature extraction method. In this study, the maximum signal to noise ratio (Max-SNR) has been used for feature extraction, which rarely applied in this area. This study presents a novel feature extraction technique, named spatio-temporal Max-SNR (ST.Max-SNR). Unlike the standard Max-SNR which only uses spatial patterns of a signal, the proposed method, separately consider the spatial and temporal patterns of the signal to enhance the accuracy of feature extraction. Due to the similarity of the common spatial pattern (CSP) and the Max-SNR algorithms, the performance of this technique and its extension, common Spatio- temporal pattern (CSTP), has been compared with the proposed method. Then, the LDA and SWLDA classifiers are used for classification of the features. Our experimental results show that the Max-SNR based spatio-temporal features lead to an average classification accuracy of 94.4 percent suggesting the best performance.
Słowa kluczowe
PL system BCI   wspólny wzorzec przestrzenny   Max-SNR  
EN BCI systems   common spatial pattern   Max-SNR   P300 component  
Wydawca Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences
Czasopismo Biocybernetics and Biomedical Engineering
Rocznik 2017
Tom Vol. 37, no. 3
Strony 365--372
Opis fizyczny Bibliogr. 26 poz., rys., tab., wykr.
autor Rizi, F. S.
autor Abootalebi, V.
autor Sadeghi, M. T.
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PL Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Kolekcja BazTech
Identyfikator YADDA bwmeta1.element.baztech-122e64c1-e4ca-443e-95bb-c4aacc8d7eb4
DOI 10.1016/j.bbe.2016.11.001