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Erschienen in:
2016 | OriginalPaper | Buchkapitel
Detecting Rare Visual and Auditory Events from EEG Using Pairwise-Comparison Neural Networks
verfasst von : Min Wang, Hussein A. Abbass, Jiankun Hu, Kathryn Merrick
Erschienen in: Advances in Brain Inspired Cognitive Systems
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Abstract
Detection of unanticipated and rare events refers to a process of identifying an occasional target (oddball) stimulus from a regular trail of standard stimuli based on brain wave signals. It is the premise of human event-related potential (ERP) applications, a significant research topic in brain computer interfaces. The focus of this paper is to investigate whether unanticipated and rare visual and auditory events are detectable from EEG signals. In order to achieve this, an exploratory experiment is conducted. A novel pairwise comparison neural network approach to detect those unanticipated and rare visual and auditory events from EEG signals is introduced. Results indicate that the change in EEG signals caused by unanticipated rare events is detectable; a piece of finding that opens opportunities for ERP-based applications.