This work presents the use of swarm intelligence algorithms as a reliable method for the optimization of electroencephalogram signals for the improvement of the performance of the brain interfaces based on stable states visual events. The preprocessing of brain signals for the extraction of characteristics and the detection of events is of paramount importance for the improvement of brain interfaces. The proposed ant colony optimization algorithm presents an improvement in obtaining the key features of the signals and the detection of events based on visual stimuli. As a reference model, we used the Independent Component Analysis method, which has been used in recent research for the removal of nonrelevant and detection of relevant data from the brain's electrical signals and also allows the collection of information in response to a stimulus and separates the signals that were generated independently in certain zones of the brain.
A set of electroencephalogram (EEG) data from 29 subjects obtained from a study, in which the subjects performed a set of tests based on visual stimuli and motor images of the hands is presented. Three types of data are provided in this article: (1) Signals based on visual events (VEP), (2) signals based on steady state visual events (SSVEP) and (3) signals based upon Motor Imagery (MI). Several research projects have used this data to test the detection of visual stimuli, classification and selection of characteristics of brain signals, EEG preprocessing and for optimization processes based on heuristic algorithms and algorithms based upon collective animal intelligence. The data was acquired using an Emotiv Epoc + portable EEG with 14 data channels and two reference channels.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.