Detecting rare visual and auditory events from EEG using pairwise-comparison neural networks

Min Wang, Hussein A. Abbass, Jiankun Hu, Kathryn Merrick

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

4 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationAdvances in Brain Inspired Cognitive Systems - 8th International Conference, BICS 2016, Proceedings
EditorsCheng-Lin Liu, Yi Zeng, Zhaoxiang Zhang, Kay Chen Tan, Bin Luo, Amir Hussain
PublisherSpringer-Verlag London Ltd.
Pages90-101
Number of pages12
ISBN (Print)9783319496849
DOIs
Publication statusPublished - 2016
Externally publishedYes
Event8th International Conference on Brain Inspired Cognitive Systems, BICS 2016 - Beijing, China
Duration: 28 Nov 201630 Nov 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10023 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Brain Inspired Cognitive Systems, BICS 2016
Country/TerritoryChina
CityBeijing
Period28/11/1630/11/16

Fingerprint

Dive into the research topics of 'Detecting rare visual and auditory events from EEG using pairwise-comparison neural networks'. Together they form a unique fingerprint.

Cite this