Brain-Computer Interfaces: Investigating the Transition from Visually Evoked to Purely Imagined Steady-State Potentials

TL;DR

This paper explores the potential of using purely imagined stimuli to generate frequency-specific EEG responses for brain-computer interfaces, aiming to replace external visual stimuli and expand application scenarios.

Contribution

It demonstrates that EEG signals can exhibit frequency-specific peaks during visual imagery, enabling a new BCI modality based on imagined stimuli.

Findings

EEG signals show frequency-specific peaks during visual imagery.

Promising classification accuracy achieved with imagined stimuli.

Potential for a robust, stimulus-free BCI modality.

Abstract

Brain-Computer Interfaces (BCIs) based on Steady State Visually Evoked Potentials (SSVEPs) have proven effective and provide significant accuracy and information-transfer rates. This family of strategies, however, requires external devices that provide the frequency stimuli required by the technique. This limits the scenarios in which they can be applied, especially when compared to other BCI approaches. In this work, we have investigated the possibility of obtaining frequency responses in the EEG output based on the pure visual imagination of SSVEP-eliciting stimuli. Our results show that not only that EEG signals present frequency-specific peaks related to the frequency the user is focusing on, but also that promising classification accuracy can be achieved, paving the way for a robust and reliable visual imagery BCI modality.