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

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

doi:10.1007/978-3-319-49685-6_9

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 Book › Conference contribution › peer-review

5 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 language	English
Title of host publication	Advances in Brain Inspired Cognitive Systems - 8th International Conference, BICS 2016, Proceedings
Editors	Cheng-Lin Liu, Yi Zeng, Zhaoxiang Zhang, Kay Chen Tan, Bin Luo, Amir Hussain
Publisher	Springer
Pages	90-101
Number of pages	12
ISBN (Print)	9783319496849
DOIs	https://doi.org/10.1007/978-3-319-49685-6_9
Publication status	Published - 2016
Externally published	Yes
Event	8th International Conference on Brain Inspired Cognitive Systems, BICS 2016 - Beijing, China Duration: 28 Nov 2016 → 30 Nov 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10023 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	8th International Conference on Brain Inspired Cognitive Systems, BICS 2016
Country/Territory	China
City	Beijing
Period	28/11/16 → 30/11/16

Access to Document

10.1007/978-3-319-49685-6_9

Cite this

Wang, M., Abbass, H. A., Hu, J., & Merrick, K. (2016). Detecting rare visual and auditory events from EEG using pairwise-comparison neural networks. In C-L. Liu, Y. Zeng, Z. Zhang, K. C. Tan, B. Luo, & A. Hussain (Eds.), Advances in Brain Inspired Cognitive Systems - 8th International Conference, BICS 2016, Proceedings (pp. 90-101). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10023 LNAI). Springer. https://doi.org/10.1007/978-3-319-49685-6_9

Wang, Min ; Abbass, Hussein A. ; Hu, Jiankun et al. / Detecting rare visual and auditory events from EEG using pairwise-comparison neural networks. Advances in Brain Inspired Cognitive Systems - 8th International Conference, BICS 2016, Proceedings. editor / Cheng-Lin Liu ; Yi Zeng ; Zhaoxiang Zhang ; Kay Chen Tan ; Bin Luo ; Amir Hussain. Springer, 2016. pp. 90-101 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{95cc85468ae648e78670c519c1453659,

title = "Detecting rare visual and auditory events from EEG using pairwise-comparison neural networks",

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.",

keywords = "Electroencephalogram (EEG), Event-related potential (ERP), Pairwise-comparison neural networks, Unanticipated events",

author = "Min Wang and Abbass, {Hussein A.} and Jiankun Hu and Kathryn Merrick",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2016.; 8th International Conference on Brain Inspired Cognitive Systems, BICS 2016 ; Conference date: 28-11-2016 Through 30-11-2016",

year = "2016",

doi = "10.1007/978-3-319-49685-6_9",

language = "English",

isbn = "9783319496849",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer",

pages = "90--101",

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}

Wang, M, Abbass, HA, Hu, J & Merrick, K 2016, Detecting rare visual and auditory events from EEG using pairwise-comparison neural networks. in C-L Liu, Y Zeng, Z Zhang, KC Tan, B Luo & A Hussain (eds), Advances in Brain Inspired Cognitive Systems - 8th International Conference, BICS 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10023 LNAI, Springer, pp. 90-101, 8th International Conference on Brain Inspired Cognitive Systems, BICS 2016, Beijing, China, 28/11/16. https://doi.org/10.1007/978-3-319-49685-6_9

Detecting rare visual and auditory events from EEG using pairwise-comparison neural networks. / Wang, Min; Abbass, Hussein A.; Hu, Jiankun et al.
Advances in Brain Inspired Cognitive Systems - 8th International Conference, BICS 2016, Proceedings. ed. / Cheng-Lin Liu; Yi Zeng; Zhaoxiang Zhang; Kay Chen Tan; Bin Luo; Amir Hussain. Springer, 2016. p. 90-101 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10023 LNAI).

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

TY - GEN

T1 - Detecting rare visual and auditory events from EEG using pairwise-comparison neural networks

AU - Wang, Min

AU - Abbass, Hussein A.

AU - Hu, Jiankun

AU - Merrick, Kathryn

N1 - Publisher Copyright: © Springer International Publishing AG 2016.

PY - 2016

Y1 - 2016

N2 - 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.

AB - 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.

KW - Electroencephalogram (EEG)

KW - Event-related potential (ERP)

KW - Pairwise-comparison neural networks

KW - Unanticipated events

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DO - 10.1007/978-3-319-49685-6_9

M3 - Conference contribution

AN - SCOPUS:84997107049

SN - 9783319496849

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 90

EP - 101

BT - Advances in Brain Inspired Cognitive Systems - 8th International Conference, BICS 2016, Proceedings

A2 - Liu, Cheng-Lin

A2 - Zeng, Yi

A2 - Zhang, Zhaoxiang

A2 - Tan, Kay Chen

A2 - Luo, Bin

A2 - Hussain, Amir

PB - Springer

T2 - 8th International Conference on Brain Inspired Cognitive Systems, BICS 2016

Y2 - 28 November 2016 through 30 November 2016

ER -

Wang M, Abbass HA, Hu J, Merrick K. Detecting rare visual and auditory events from EEG using pairwise-comparison neural networks. In Liu C-L, Zeng Y, Zhang Z, Tan KC, Luo B, Hussain A, editors, Advances in Brain Inspired Cognitive Systems - 8th International Conference, BICS 2016, Proceedings. Springer. 2016. p. 90-101. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-49685-6_9

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

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