Single-Option P300-BCI Performance Is Affected by Visual Stimulation Conditions
| Autor: | Javier M. Antelis, Omar Mendoza-Montoya, Juan David Chailloux Peguero |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
genetic structures
Computer science 0206 medical engineering Stimulation 02 engineering and technology Stimulus (physiology) lcsh:Chemical technology Biochemistry Article visual stimuli paradigm Analytical Chemistry 03 medical and health sciences 0302 clinical medicine Humans lcsh:TP1-1185 Electrical and Electronic Engineering Instrumentation Brain–computer interface business.industry Reproducibility of Results Pattern recognition Event-Related Potentials P300 020601 biomedical engineering Atomic and Molecular Physics and Optics Brain-Computer Interfaces performance assessment Artificial intelligence business P300 BCI Photic Stimulation 030217 neurology & neurosurgery |
| Zdroj: | Sensors Volume 20 Issue 24 Sensors (Basel, Switzerland) Sensors, Vol 20, Iss 7198, p 7198 (2020) |
| ISSN: | 1424-8220 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
| Nepřihlášeným uživatelům se plný text nezobrazuje | K zobrazení výsledku je třeba se přihlásit. |