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Frequency- and Phase Encoded SSVEP Using Spatiotemporal Beamforming.

ABSTRACT: In brain-computer interfaces (BCIs) based on steady-state visual evoked potentials (SSVEPs) the number of selectable targets is rather limited when each target has its own stimulation frequency. One way to remedy this is by combining frequency- with phase encoding. We introduce a new multivariate spatiotemporal filter, based on Linearly Constrained Minimum Variance (LCMV) beamforming, for discriminating between frequency-phase encoded targets more accurately, even when using short signal lengths than with (extended) Canonical Correlation Analysis (CCA), which is traditionally posited for this stimulation paradigm.

SUBMITTER: Wittevrongel B

PROVIDER: S-EPMC4972379 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Frequency- and Phase Encoded SSVEP Using Spatiotemporal Beamforming.

Wittevrongel Benjamin B Van Hulle Marc M MM

PloS one 20160803 8

In brain-computer interfaces (BCIs) based on steady-state visual evoked potentials (SSVEPs) the number of selectable targets is rather limited when each target has its own stimulation frequency. One way to remedy this is by combining frequency- with phase encoding. We introduce a new multivariate spatiotemporal filter, based on Linearly Constrained Minimum Variance (LCMV) beamforming, for discriminating between frequency-phase encoded targets more accurately, even when using short signal lengths ...[more]

PMID: 27486801

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