Abstract
The N2pc is a lateralised Event-Related Potential (ERP) that signals a shift of attention towards the location of a potential object of interest. We propose a single-trial target-localisation collaborative Brain-Computer Interface (cBCI) that exploits this ERP to automatically approximate the horizontal position of targets in aerial images. Images were presented by means of the rapid serial visual presentation technique at rates of 5, 6 and 10 Hz. We created three different cBCIs and tested a participant selection method in which groups are formed according to the similarity of participants’ performance. The N2pc that is elicited in our experiments contains information about the position of the target along the horizontal axis. Moreover, combining information from multiple participants provides absolute median improvements in the area under the receiver operating characteristic curve of up to 21% (for groups of size 3) with respect to single-user BCIs. These improvements are bigger when groups are formed by participants with similar individual performance, and much of this effect can be explained using simple theoretical models. Our results suggest that BCIs for automated triaging can be improved by integrating two classification systems: one devoted to target detection and another to detect the attentional shifts associated with lateral targets.
Highlights
A Brain-Computer Interface (BCI) is a system that allows users to convey commands to interact with external devices using only their thoughts, usually by means of electroencephalography (EEG) signals recorded from their scalp
In previous work [29, 30], we showed that the N2pc is elicited in the conditions of the RSVP paradigm with real aerial images, and that it can be used to discriminate targets depending on ths side of an image where they are located in single-user BCIs
We will address the matter of the performance of single-user BCIs and collaborative Brain-Computer Interface (cBCI) for the left vs right single-trial classification of targets in images that are known to contain one, and a theoretical analysis of the reasons behind the improvements that are obtained by the cBCI over the sBCIs
Summary
A Brain-Computer Interface (BCI) is a system that allows users to convey commands to interact with external devices using only their thoughts, usually by means of electroencephalography (EEG) signals recorded from their scalp. Some BCI systems developed over the last decade have shifted their attention towards able-bodied users, in an attempt to augment human abilities. One type of such systems consists of creating collaborative BCIs (cBCIs) by grouping users (e.g., by fusing information extracted from their individual EEG recordings) with the aim of better controlling an external device or improving their individual performance at a joint task [5,6,7,8,9,10,11,12].
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