Modeling the mental differentiation task with EEG

Tan Vo; Tom Gedeon; Dat Tran

doi:10.1007/978-3-642-34481-7_44

Modeling the mental differentiation task with EEG

Tan Vo^*, Tom Gedeon, Dat Tran

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

Differentiation in human beings is the act of perceiving the difference in or between objects. In other words, it is the mental process taking place to discriminate one thing from others, a common task performed by a person on a very regular basis. Making such differentiations, small or large, easy or hard, still requires a combination of cognitive processes to occur across various parts of the human brain. In this paper, an EEG-based BCI experiment was organized to study the detection of such cognitive processes. Utilizing a machine learning tool, Artificial Neural Networks, to aid in analyzing the acquired dataset, a high correct classification rate was achieved, confirming that it is possible to computationally detect these differentiation activities from EEG signals.

Original language	English
Title of host publication	Neural Information Processing - 19th International Conference, ICONIP 2012, Proceedings
Pages	357-364
Number of pages	8
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-642-34481-7_44
Publication status	Published - 2012
Event	19th International Conference on Neural Information Processing, ICONIP 2012 - Doha, Qatar Duration: 12 Nov 2012 → 15 Nov 2012

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	7664 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	19th International Conference on Neural Information Processing, ICONIP 2012
Country/Territory	Qatar
City	Doha
Period	12/11/12 → 15/11/12

Access to Document

10.1007/978-3-642-34481-7_44

Cite this

Vo, T., Gedeon, T., & Tran, D. (2012). Modeling the mental differentiation task with EEG. In Neural Information Processing - 19th International Conference, ICONIP 2012, Proceedings (PART 2 ed., pp. 357-364). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7664 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-34481-7_44

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title = "Modeling the mental differentiation task with EEG",

abstract = "Differentiation in human beings is the act of perceiving the difference in or between objects. In other words, it is the mental process taking place to discriminate one thing from others, a common task performed by a person on a very regular basis. Making such differentiations, small or large, easy or hard, still requires a combination of cognitive processes to occur across various parts of the human brain. In this paper, an EEG-based BCI experiment was organized to study the detection of such cognitive processes. Utilizing a machine learning tool, Artificial Neural Networks, to aid in analyzing the acquired dataset, a high correct classification rate was achieved, confirming that it is possible to computationally detect these differentiation activities from EEG signals.",

keywords = "Artifical neural network, BCI, Biosignal processing, Differencitation tasks, EEG",

author = "Tan Vo and Tom Gedeon and Dat Tran",

year = "2012",

doi = "10.1007/978-3-642-34481-7_44",

language = "English",

isbn = "9783642344800",

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

number = "PART 2",

pages = "357--364",

booktitle = "Neural Information Processing - 19th International Conference, ICONIP 2012, Proceedings",

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note = "19th International Conference on Neural Information Processing, ICONIP 2012 ; Conference date: 12-11-2012 Through 15-11-2012",

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Vo, T, Gedeon, T & Tran, D 2012, Modeling the mental differentiation task with EEG. in Neural Information Processing - 19th International Conference, ICONIP 2012, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 7664 LNCS, pp. 357-364, 19th International Conference on Neural Information Processing, ICONIP 2012, Doha, Qatar, 12/11/12. https://doi.org/10.1007/978-3-642-34481-7_44

Modeling the mental differentiation task with EEG. / Vo, Tan; Gedeon, Tom; Tran, Dat.
Neural Information Processing - 19th International Conference, ICONIP 2012, Proceedings. PART 2. ed. 2012. p. 357-364 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7664 LNCS, No. PART 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Gedeon, Tom

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AB - Differentiation in human beings is the act of perceiving the difference in or between objects. In other words, it is the mental process taking place to discriminate one thing from others, a common task performed by a person on a very regular basis. Making such differentiations, small or large, easy or hard, still requires a combination of cognitive processes to occur across various parts of the human brain. In this paper, an EEG-based BCI experiment was organized to study the detection of such cognitive processes. Utilizing a machine learning tool, Artificial Neural Networks, to aid in analyzing the acquired dataset, a high correct classification rate was achieved, confirming that it is possible to computationally detect these differentiation activities from EEG signals.

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Vo T, Gedeon T, Tran D. Modeling the mental differentiation task with EEG. In Neural Information Processing - 19th International Conference, ICONIP 2012, Proceedings. PART 2 ed. 2012. p. 357-364. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-34481-7_44

Modeling the mental differentiation task with EEG

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