SSVEP detection assessment by combining visual stimuli paradigms and no-training detection methods

Frontiers in Neuroscience

Neuroscience

Luis G. Hernández-Rojas¹  Javier M. Antelis¹  Juan David Chailloux Peguero¹  Omar Mendoza-Montoya¹  Ricardo Caraza² 

[1] Tecnologico de Monterrey, School of Engineering and Sciences, Monterrey, Mexico;Tecnologico de Monterrey, School of Medicine and Health Sciences, Monterrey, Mexico;

关键词: SSVEP detection method;    SSVEP visual paradigm;    BCI-user comfort;    Brain-Computer Interface;    electroencephalography;    evoked potentials;    biomedical signal processing;   

DOI  :  10.3389/fnins.2023.1142892

 received in 2023-01-12, accepted in 2023-04-25,  发布年份 2023

来源: Frontiers

【 摘 要 】

IntroductionBrain-Computer Interfaces (BCI) based on Steady-State Visually Evoked Potentials (SSVEP) have great potential for use in communication applications because of their relatively simple assembly and in some cases the possibility of bypassing the time-consuming training stage. However, among multiple factors, the efficient performance of this technology is highly dependent on the stimulation paradigm applied in combination with the SSVEP detection algorithm employed. This paper proposes the performance assessment of the classification of target events with respect to non-target events by applying four types of visual paradigms, rectangular modulated On-Off (OOR), sinusoidal modulated On-Off (OOS), rectangular modulated Checkerboard (CBR), and sinusoidal modulated Checkerboard (CBS), with three types of SSVEP detection methods, Canonical Correlation Analysis (CCA), Filter-Bank CCA (FBCCA), and Minimum Energy Combination (MEC).MethodsWe set up an experimental protocol in which the four types of visual stimuli were presented randomly to twenty-seven participants and after acquiring their electroencephalographic responses to five stimulation frequencies (8.57, 10.909, 15, 20, and 24 Hz), the three detection methods were applied to the collected data.ResultsThe results are conclusive, obtaining the best performance with the combination of either OOR or OOS visual stimulus and the FBCCA as a detection method, however, this finding contrasts with the opinion of almost half of the participants in terms of visual comfort, where the 51.9% of the subjects felt more comfortable and focused with CBR or CBS stimulation.DiscussionFinally, the EEG recordings correspond to the SSVEP response of 27 subjects to four visual paradigms when selecting five items on a screen, which is useful in BCI navigation applications. The dataset is available to anyone interested in studying and evaluating signal processing and machine-learning algorithms for SSVEP-BCI systems.

【 授权许可】

Unknown   
Copyright © 2023 Chailloux Peguero, Hernández-Rojas, Mendoza-Montoya, Caraza and Antelis.