Next Article in Journal
Near-Field to Far-Field RCS Prediction on Arbitrary Scanning Surfaces Based on Spherical Wave Expansion
Next Article in Special Issue
Deep and Wide Transfer Learning with Kernel Matching for Pooling Data from Electroencephalography and Psychological Questionnaires
Previous Article in Journal
Air-Coupled Ultrasonic Probe Integrity Test Using a Focused Transducer with Similar Frequency and Limited Aperture for Contrast Enhancement
Previous Article in Special Issue
Cross-Frequency Power-Power Coupling Analysis: A Useful Cross-Frequency Measure to Classify ICA-Decomposed EEG

Single-Option P300-BCI Performance Is Affected by Visual Stimulation Conditions

Tecnologico de Monterrey, School of Engineering and Science, Monterrey, NL 64849, Mexico
Author to whom correspondence should be addressed.
Current address: Avenida Eugenio Garza Sada 2501, Monterrey, NL 64849, Mexico.
These authors contributed equally to this work.
Sensors 2020, 20(24), 7198;
Received: 6 November 2020 / Revised: 8 December 2020 / Accepted: 10 December 2020 / Published: 16 December 2020
The P300 paradigm is one of the most promising techniques for its robustness and reliability in Brain-Computer Interface (BCI) applications, but it is not exempt from shortcomings. The present work studied single-trial classification effectiveness in distinguishing between target and non-target responses considering two conditions of visual stimulation and the variation of the number of symbols presented to the user in a single-option visual frame. In addition, we also investigated the relationship between the classification results of target and non-target events when training and testing the machine-learning model with datasets containing different stimulation conditions and different number of symbols. To this end, we designed a P300 experimental protocol considering, as conditions of stimulation: the color highlighting or the superimposing of a cartoon face and from four to nine options. These experiments were carried out with 19 healthy subjects in 3 sessions. The results showed that the Event-Related Potentials (ERP) responses and the classification accuracy are stronger with cartoon faces as stimulus type and similar irrespective of the amount of options. In addition, the classification performance is reduced when using datasets with different type of stimulus, but it is similar when using datasets with different the number of symbols. These results have a special connotation for the design of systems, in which it is intended to elicit higher levels of evoked potentials and, at the same time, optimize training time. View Full-Text
Keywords: P300 BCI; performance assessment; visual stimuli paradigm P300 BCI; performance assessment; visual stimuli paradigm
Show Figures

Figure 1

MDPI and ACS Style

Chailloux Peguero, J.D.; Mendoza-Montoya, O.; Antelis, J.M. Single-Option P300-BCI Performance Is Affected by Visual Stimulation Conditions. Sensors 2020, 20, 7198.

AMA Style

Chailloux Peguero JD, Mendoza-Montoya O, Antelis JM. Single-Option P300-BCI Performance Is Affected by Visual Stimulation Conditions. Sensors. 2020; 20(24):7198.

Chicago/Turabian Style

Chailloux Peguero, Juan D., Omar Mendoza-Montoya, and Javier M. Antelis. 2020. "Single-Option P300-BCI Performance Is Affected by Visual Stimulation Conditions" Sensors 20, no. 24: 7198.

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop