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Effects of the concentration level, eye fatigue and coffee consumption on the performance of a BCI system based on visual ERP-P300 by Cristian Felipe Blanco-Díaz; Cristian David Guerrero-Méndez; Teodiano Bastos-Filho; Sebastián Jaramillo-Isaza; Andrés Felipe Ruiz-Olaya is a Neuroscience article available to read on EtoBox.

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## Background: A widely used paradigm for brain-computer interfaces (bci) is based on detecting p300 event-related potentials (erps) in response to stimulation and concentration tasks. an open challenge corresponds to maximizing the performance of a bci by considering artifacts arising from the user's cognitive and physical conditions during task execution. ## New method: In this study, an analysis of the performance of a visual bci-p300 system was performed under the metrics of sensitivity (sen), specificity (spe), accuracy (acc), and area-under the roc curve (auc), considering the main reported factors affecting the neurophysiological behavior of the p300 signal: concentration level, eye fatigue, and coffee consumption. ## Comparison with existing methods: We compared the performance of three p300 signal detection methods (ma-lda, cca-rlr, and ma+cca-rlr) using a public database (gigascience) in different groups. data were segmented according to three factors of interest: high and low levels of concentration, high and low eye fatigue, and coffee consumption at different times. ## Results: The results showed a significant improvement between 3% and 6% for the metrics evaluated for

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Author

Cristian Felipe Blanco-Díaz; Cristian David Guerrero-Méndez; Teodiano Bastos-Filho; Sebastián Jaramillo-Isaza; Andrés Felipe Ruiz-Olaya

Publisher

Elsevier BV

Published

2022

Language

EN

Field

Neuroscience (Life Sciences)