Brain-Computer Interface: comparison of two control modes to drive a virtual robot

A Brain-Computer Interface (BCI) is a system that enables communication and control that is not based on muscular movements, but on brain activity. Some of these systems are based on discrimination of different mental tasks; usually they match the number of mental tasks to the number of control commands. Previous research at the University of Málaga (UMA-BCI) have proposed a BCI system to freely control an external device, letting the subjects choose among several navigation commands using only one active mental task (versus any other mental activity). Although the navigation paradigm proposed in this system has been proved useful for continuous movements, if the user wants to move medium or large distances, he/she needs to keep the effort of the MI task in order to keep the command. In this way, the aim of this work was to test a navigation paradigm based on the brain-switch mode for ‘forward’ command. In this mode, the subjects used the mental task to switch their state on /off: they stopped if they were moving forward and vice versa. Initially, twelve healthy and untrained subjects participated in this study, but due to a lack of control in previous session, only four subjects participated in the experiment, in which they had to control a virtual robot using two paradigms: one based on continuous mode and another based on switch mode. Preliminary results show that both paradigms can be used to navigate through virtual environments, although with the first one the times needed to complete a path were notably lower.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Control de un teclado virtual por un paciente de ela mediante el uso de dos tecnologías: eyetracker y sistema BCI

Pacientes que sufren de Esclerosis Lateral Amiotrófica (ELA) pueden llegar a sufrir lo que se conoce como síndrome de enclaustramiento (Locked-in-syndrome, LIS), caracterizado, en su modalidad clásica, por la imposibilidad de realizar cualquier movimiento salvo parpadear y mover los ojos. Para estos pacientes, la tecnología asistida disponible es muy limitada, siendo aquellas basadas en el eyetracker (seguimiento de ojos) y en el BCI las más apropiadas.Varios estudios han tratado de comparar ambas tecnologías. En el caso de controlar un sistema de comunicación, estos concluyen que un eyetracker es más ventajoso. Precisamente, el objetivo del estudio que se propone en esta contribución es demostrar que el uso de la tecnología puede depender de las preferencias de cada usuario. Para ello se lleva a cabo un estudio comparativo entre el uso de un eyetracker (Tobii modelo C15) y una Interfaz Cerebro-Computadora basado en la detección del potencial P300 para controlar un teclado virtual. Dicho estudio se realiza sobre un paciente con ELA. El estudio de las prestaciones de ambos sistemas en términos de error y tiempo, además de la carga de trabajo y de otras medidas subjetivas, nos permitirán determinar la usabilidad de ambos sistemas y obtener resultados sobre dicha comparativaUniversidad de Málaga Campus de Excelencia Internacional Andalucía Tech

BRAIN-COMPUTER INTERFACE: COMPARISON OF TWO CONTROL MODES TO DRIVE A VIRTUAL ROBOT

A Brain-Computer Interface (BCI) is a system that enables communication and control that is not based on muscular movements, but on brain activity. Some of these systems are based on discrimination of different mental tasks; usually they match the number of mental tasks to the number of control commands. Previous research at the University of Málaga (UMABCI) have proposed a BCI system to freely control an external device, letting the subjects choose among several navigation commands using only one active mental task (versus any other mental activity). Although the navigation paradigm proposed in this system has been proved useful for continuous movements, if the user wants to move medium or large distances, he/she needs to keep the effort of the MI task in order to keep the command. In this way, the aim of this work was to test a navigation paradigm based on the brain-switch mode for ‘forward’ command. In this mode, the subjects used the mental task to switch their state on /off: they stopped if they were moving forward and vice versa. Initially, twelve healthy and untrained subjects participated in this study, but due to a lack of control in previous session, only four subjects participated in the experiment, in which they had to control a virtual robot using two paradigms: one based on continuous mode and another based on switch mode. Preliminary results show that both paradigms can be used to navigate through virtual environments, although with the first one the times needed to complete a path were notably lower

BRAIN-COMPUTER INTERFACE: COMPARISON OF TWO CONTROL MODES TO DRIVE A VIRTUAL ROBOT

A Brain-Computer Interface (BCI) is a system that enables communication and control that is not based on muscular movements, but on brain activity. Some of these systems are based on discrimination of different mental tasks; usually they match the number of mental tasks to the number of control commands. Previous research at the University of Málaga (UMABCI) have proposed a BCI system to freely control an external device, letting the subjects choose among several navigation commands using only one active mental task (versus any other mental activity). Although the navigation paradigm proposed in this system has been proved useful for continuous movements, if the user wants to move medium or large distances, he/she needs to keep the effort of the MI task in order to keep the command. In this way, the aim of this work was to test a navigation paradigm based on the brain-switch mode for ‘forward’ command. In this mode, the subjects used the mental task to switch their state on /off: they stopped if they were moving forward and vice versa. Initially, twelve healthy and untrained subjects participated in this study, but due to a lack of control in previous session, only four subjects participated in the experiment, in which they had to control a virtual robot using two paradigms: one based on continuous mode and another based on switch mode. Preliminary results show that both paradigms can be used to navigate through virtual environments, although with the first one the times needed to complete a path were notably lower

Exploring a P300 Brain-Computer Interface Based on Three Different RSVP Paradigms

A BCI Speller is a typical Brain-Computer Interface (BCI) system for communication purpose. This technology can provide users with severe motor disability with an assistive device controlled by brain activity. In the present preliminary study we investigated, in five subjects, the performance and the Information Transfer Rate (ITR) based on three different Rapid Serial Visual Presentation (RSVP) paradigms to control a BCI speller. The variants of the three paradigms were the stimuli presented: letters, images and famous faces. These preliminary results showed that performance can increase when using an RSVP paradigm based on images, and ITR can improves when using the images and the famous faces paradigms.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Usability of three software platforms for modifying graphical layout in visual P300-based brain-computer interface

Individuals afflicted by neurodegenerative conditions such as amyotrophic lateral sclerosis may eventually reach a point where they lose the ability to communicate with the outside world through conventional muscular pathways. In these cases, brain-computer interfaces (BCIs) can be a suitable alternative, as they directly transform brain activity into external commands. A P300-based speller is a BCI for communication purposes. The most popular software platforms used to develop spellers are BCI2000 and Open-ViBE. However, these platforms can be relatively complex to set up without advanced technical knowledge. For this reason, the UMA-BCI Speller platform was recently developed, intended to facilitate the control of the system. Hence, the objective of this research was to assess and compare the user-friendliness of the three platforms put forth. A group of fifteen participants were tasked with configuring a designated speller layout using the three platforms. The findings acquired demonstrated that the UMA-BCI Speller platform exhibited the utmost level of usability, as it required the shortest time to complete the tasks and received the best feedback in the questionnaires. Overall, there was no difference between the BCI2000 and Open-ViBE platforms. In short, the UMA-BCI Speller offered the best usability and showed itself to be an easy application to use that provides many options to configure a speller graphical layout.Funding for open access charge: Universidad de Málaga / CBUA

Classification de variables et analyse multivariée de données mixtes issues d’une étude BCI

International audienceL'objectif de ce travail est de traiter des données complexes issues de la technique des Brain Computer Interfaces (BCI) au moyen de méthodes statistiques multivariées (approche PCAmix et classification de variables) afin de mieux comprendre et interpréter les relations qui existent entre elles. Cet article présente ainsi la classification de variables qui a pour but de réunir des variables fortement liées entre elles. L'approche proposée fonctionne avec des données mixtes, c'est à dire des données contenant des variables numériques et des variables catégorielles. Deux algorithmes de classification de variables sont décrits : un de classification hiérarchique et un autre de partitionnement de type k-means. Une rapide description de la méthode PCAmix (qui permet de faire de l'analyse en composantes principales pour des données mixtes) est fournie, vu que le calcul des variables synthétiques résumant les classes de variables obtenues est fondé sur cette méthode multivariée. Enfin, les approches PCAmix et ClustOfVar (implémentées dans les packages R ClustOfVar et PCAmixdata) sont mises en oeuvre sur les données réelles issues de l'étude BCI. Des recommandations, reposant non seulement sur des critères de performances, d'efficience mais aussi de satisfaction, ont pu être faites concernant le choix d'interface dans l'usage des claviers virtuels, notamment pour des personnes avec des problèmes moteurs tels que la maladie de Charcot. ABSTRACT. The aim of this work is to analyze complex data from a Brain Computer Interfaces (BCI) study using multivariate statistical methods (PCAmix approach and clustering of variables) to better understand and interpret their relationships. This article presents clustering of variables which aim is to lump together strongly related variables. The proposed approach works on a mixed data set, i.e. on a data set which contains numerical variables and categorical variables. Two algorithms of clustering of variables are described : a hierarchical clustering and a k-means type clustering. A brief description of PCAmix method (that is a principal component analysis for mixed data) is provided, since the calculus of the synthetic variables summarizing the obtained clusters of variables is based on this multivariate method. Finally, the PCAmix and ClustOfVar approaches (implemented in the R packages ClustOfVar and PCAmixdata) are illustrated on a real dataset from a BCI (brain computer interface) study. Recommendations, based not only on performance, efficiency, but also on satisfaction criteria, could be made concerning the choice of interface in the use of virtual keyboards, especially for people with motor disorder such as Charcot's disease. MOTS-CLÉS. Classification de variables, données mixtes, analyse en composantes principales, packages R, brain computer interface, analyse multivariée des données, visualisation des données. KEYWORDS. clustering of variables, mixed data, principal component analysis for mixed data, R packages, brain computer interface, multivariate data analysis, data visualization

Comparison of two paradigms based on stimulation with images in a spelling brain-computer interface.

A BCI Speller is a typical Brain-Computer Interface (BCI) system for communication purposes. This technology can provide users with severe motor disability with an assistive device controlled by brain activity. The present preliminary study, with only four subjects, is focused on the control of a 5x5 P300-based speller matrix for communication purposes. In this work, we study the effect of flashing stimuli used to highlight the letters in two conditions: pictures and red famous faces (that is, famous faces coloured in red). These preliminary results, based on performance and the Information Transfer Rate (ITR), showed that both conditions are similar, obtaining very good performance compared to conventional P300-speller. In this sense, the use of pictures does not make the performance worse, allowing to develop more attractive and usable interfaces. More tests would confirm if there is a difference in performance between the two conditions proposed.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Comparison of Two Paradigms Based on Stimulation with Images in a Spelling Brain–Computer Interface

A P300-based speller can be used to control a home automation system via brain activity. Evaluation of the visual stimuli used in a P300-based speller is a common topic in the field of brain–computer interfaces (BCIs). The aim of the present work is to compare, using the usability approach, two types of stimuli that have provided high performance in previous studies. Twelve participants controlled a BCI under two conditions, which varied in terms of the type of stimulus employed: a red famous face surrounded by a white rectangle (RFW) and a range of neutral pictures (NPs). The usability approach included variables related to effectiveness (accuracy and information transfer rate), efficiency (stress and fatigue), and satisfaction (pleasantness and System Usability Scale and Affect Grid questionnaires). The results indicated that there were no significant differences in effectiveness, but the system that used NPs was reported as significantly more pleasant. Hence, since satisfaction variables should also be considered in systems that potential users are likely to employ regularly, the use of different NPs may be a more suitable option than the use of a single RFW for the development of a home automation system based on a visual P300-based speller.This work was partially supported by the project PID2021-127261OB-I00 (SICODIS), funded by MCIN (Ministerio de Ciencia e Innovación)/AEI (Agencia Estatal de Investigación)/10.13039/501100011033/FEDER, UE (Fondo Europeo de Desarrollo Regional). The work was also partially supported by the University of Málaga (Universidad de Málaga). Partial funding for open access charge: Universidad de Málag

Evaluation of Different Types of Stimuli in a ERP-Based Brain-Computer Interface Speller under RSVP.

Rapid Serial Visual Presentation (RSVP) is currently one of the most suitable gaze-independent paradigms to control a visual brain-computer interface based on event related potentials (ERP-BCI) by patients with a lack of ocular motility. However, gaze-independent paradigms have not been studied as closely as gaze-dependent ones in reference to the type of stimuli presented. Under gaze-dependent paradigms, faces have been shown to be the most appropriate stimuli, especially when they are red. Therefore, the aim of the present work is to evaluate whether these results of the color of faces as visual stimuli also has an impact on ERP-BCI performance under the RSVP paradigm. In this preliminary study, six participants tested the ERP-BCI under RSVP using four different conditions for a speller application: letters, blue faces, red faces, and green faces. These preliminary results showed non-significant differences in accuracy or information transfer rate. The present work therefore shows that, unlike under gaze-dependent paradigms, the stimulus type has no impact on the performance of an ERP-BCI under RSVP. This finding should be considered in future ERP-BCI proposals aimed at users who need gaze-independent systems.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech