Space-time filter for SSVEP brain-computer interface based on the minimum variance distortionless response.

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MetadadosDescriçãoIdioma
Autor(es): dc.creatorLeite, Sarah Negreiros de Carvalho-
Autor(es): dc.creatorVargas, Guilherme Vettorazzi-
Autor(es): dc.creatorCosta, Thiago Bulhões da Silva-
Autor(es): dc.creatorLeite, Harlei Miguel de Arruda-
Autor(es): dc.creatorCoradine, Luis Cláudius-
Autor(es): dc.creatorBoccato, Levy-
Autor(es): dc.creatorSoriano, Diogo Coutinho-
Autor(es): dc.creatorAttux, Romis Ribeiro de Faissol-
Data de aceite: dc.date.accessioned2025-08-21T15:34:42Z-
Data de disponibilização: dc.date.available2025-08-21T15:34:42Z-
Data de envio: dc.date.issued2022-03-08-
Data de envio: dc.date.issued2022-03-08-
Data de envio: dc.date.issued2020-
Fonte completa do material: dc.identifierhttp://www.repositorio.ufop.br/jspui/handle/123456789/14637-
Fonte completa do material: dc.identifierhttps://link.springer.com/article/10.1007%2Fs11517-021-02345-7-
Fonte completa do material: dc.identifierhttps://doi.org/10.1007/s11517-021-02345-7-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/1018783-
Descrição: dc.descriptionBrain-computer interfaces (BCI) based on steady-state visually evoked potentials (SSVEP) have been increasingly used in different applications, ranging from entertainment to rehabilitation. Filtering techniques are crucial to detect the SSVEP response since they can increase the accuracy of the system. Here, we present an analysis of a space-time filter based on the Minimum Variance Distortionless Response (MVDR). We have compared the performance of a BCISSVEP using the MVDR filter to other classical approaches: Common Average Reference (CAR) and Canonical Correlation Analysis (CCA). Moreover, we combined the CAR and MVDR techniques, totalling four filtering scenarios. Feature extraction was performed using Welch periodogram, Fast Fourier transform, and CCA (as extractor) with one and two harmonics. Feature selection was performed by forward wrappers, and a linear classifier was employed for discrimination. The main analyses were carried out over a database of ten volunteers, considering two cases: four and six visual stimuli. The results show that the BCI-SSVEP using the MVDR filter achieves the best performance among the analysed scenarios. Interestingly, the system’s accuracy using the MVDR filter is practically constant even when the number of visual stimuli was increased, whereas degradation was observed for the other techniques.-
Formato: dc.formatapplication/pdf-
Idioma: dc.languageen-
Direitos: dc.rightsrestrito-
Palavras-chave: dc.subjectBrain-computer interface-
Palavras-chave: dc.subjectSteady-state visually evoked potential-
Palavras-chave: dc.subjectSpatial filtering-
Palavras-chave: dc.subjectTemporal filtering-
Palavras-chave: dc.subjectMinimum variance distortionless response-
Título: dc.titleSpace-time filter for SSVEP brain-computer interface based on the minimum variance distortionless response.-
Aparece nas coleções:Repositório Institucional - UFOP

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