A Single-Channel SSVEP-Based BCI Speller Using Deep Learning

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Development of a Brain Computer Interface (BCI) Speller System Based on SSVEP Signals

BCI is one of the most intriguing technologies among other HCI systems, mostly because of its capability of recording brain activities. Spelling BCIs, which help paralyzed people to maintain communication, are one of the striking topics in the field of BCI. In this scientific a spelling BCI system with high transfer rate and accuracy that uses SSVEP signals is proposed.In addition, we suggested...

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Multi-target SSVEP-based BCI using Multichannel SSVEP Detection

Spatial filtering method and fast Fourier transform (FFT) based spectrum estimation method are applied to reveal the presence of steady state visual evoked potential (SSVEP) in multiple-electrodes electroencephalogram (EEG) signals used in Brain-Computer Interface (BCI) system. The SSVEP responses are elicited by visual stimuli in the form of flickering light emitting diode (LED) array and comp...

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Online SSVEP-based BCI using Riemannian geometry

Challenges for the next generation of Brain Computer Interfaces (BCI) are to mitigate the common sources of variability (electronic, electrical, biological) and to develop online and adaptive systems following the evolution of the subject's brain waves. Studying electroencephalographic (EEG) signals from their associated covariance matrices allows the construction of a representation which is i...

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Development of a Brain Computer Interface (BCI) Speller System Based on SSVEP Signals

BCI is one of the most intriguing technologies among other HCI systems, mostly because of its capability of recording brain activities. Spelling BCIs, which help paralyzed people to maintain communication, are one of the striking topics in the field of BCI. In this scientific a spelling BCI system with high transfer rate and accuracy that uses SSVEP signals is proposed. In addition, we suggeste...

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Eliciting dual-frequency SSVEP using a hybrid SSVEP-P300 BCI

BACKGROUND Steady-state visual-evoked potential (SSVEP)-based brain-computer interfaces (BCIs) generate weak SSVEP with a monitor and cannot use harmonic frequencies, whereas P300-based BCIs need multiple stimulation sequences. These issues can decrease the information transfer rate (ITR). NEW METHOD In this paper, we introduce a novel hybrid SSVEP-P300 speller that generates dual-frequency S...

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ژورنال

عنوان ژورنال: IEEE Access

سال: 2019

ISSN: 2169-3536

DOI: 10.1109/access.2018.2886759