Brain computer interfaces: A recurrent neural network approach

Gareth Oliver; Tom Gedeon

doi:10.1007/978-3-642-17534-3_9

Brain computer interfaces: A recurrent neural network approach

Gareth Oliver^*, Tom Gedeon

^*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

This paper explores the use of recurrent neural networks in the field of Brain Computer Interfaces(BCI). In particular it looks at a recurrent neural network, an echostate network and a CasPer neural network and attempts to use them to classify data from BCI competition III's dataset IVa. In addition it proposes a new method, EchoCasPer, which uses the CasPer training scheme in a recurrent neural network. The results showed that temporal information existed within the BCI data to be made use of, but further pre-processing and parameter exploration was needed to reach competitive classification rates.

Original language	English
Title of host publication	Neural Information Processing
Subtitle of host publication	Models and Applications - 17th International Conference, ICONIP 2010, Proceedings
Pages	66-73
Number of pages	8
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-642-17534-3_9
Publication status	Published - 2010
Event	17th International Conference on Neural Information Processing, ICONIP 2010 - Sydney, NSW, Australia Duration: 22 Nov 2010 → 25 Nov 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	6444 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	17th International Conference on Neural Information Processing, ICONIP 2010
Country/Territory	Australia
City	Sydney, NSW
Period	22/11/10 → 25/11/10

Access to Document

10.1007/978-3-642-17534-3_9

Cite this

Oliver, G., & Gedeon, T. (2010). Brain computer interfaces: A recurrent neural network approach. In Neural Information Processing: Models and Applications - 17th International Conference, ICONIP 2010, Proceedings (PART 2 ed., pp. 66-73). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6444 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-17534-3_9

Oliver, Gareth ; Gedeon, Tom. / Brain computer interfaces : A recurrent neural network approach. Neural Information Processing: Models and Applications - 17th International Conference, ICONIP 2010, Proceedings. PART 2. ed. 2010. pp. 66-73 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

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title = "Brain computer interfaces: A recurrent neural network approach",

abstract = "This paper explores the use of recurrent neural networks in the field of Brain Computer Interfaces(BCI). In particular it looks at a recurrent neural network, an echostate network and a CasPer neural network and attempts to use them to classify data from BCI competition III's dataset IVa. In addition it proposes a new method, EchoCasPer, which uses the CasPer training scheme in a recurrent neural network. The results showed that temporal information existed within the BCI data to be made use of, but further pre-processing and parameter exploration was needed to reach competitive classification rates.",

keywords = "BCI, CasPer, Echostate Network, RNN",

author = "Gareth Oliver and Tom Gedeon",

year = "2010",

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language = "English",

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

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Oliver, G & Gedeon, T 2010, Brain computer interfaces: A recurrent neural network approach. in Neural Information Processing: Models and Applications - 17th International Conference, ICONIP 2010, 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. 6444 LNCS, pp. 66-73, 17th International Conference on Neural Information Processing, ICONIP 2010, Sydney, NSW, Australia, 22/11/10. https://doi.org/10.1007/978-3-642-17534-3_9

Brain computer interfaces: A recurrent neural network approach. / Oliver, Gareth; Gedeon, Tom.
Neural Information Processing: Models and Applications - 17th International Conference, ICONIP 2010, Proceedings. PART 2. ed. 2010. p. 66-73 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6444 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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N2 - This paper explores the use of recurrent neural networks in the field of Brain Computer Interfaces(BCI). In particular it looks at a recurrent neural network, an echostate network and a CasPer neural network and attempts to use them to classify data from BCI competition III's dataset IVa. In addition it proposes a new method, EchoCasPer, which uses the CasPer training scheme in a recurrent neural network. The results showed that temporal information existed within the BCI data to be made use of, but further pre-processing and parameter exploration was needed to reach competitive classification rates.

AB - This paper explores the use of recurrent neural networks in the field of Brain Computer Interfaces(BCI). In particular it looks at a recurrent neural network, an echostate network and a CasPer neural network and attempts to use them to classify data from BCI competition III's dataset IVa. In addition it proposes a new method, EchoCasPer, which uses the CasPer training scheme in a recurrent neural network. The results showed that temporal information existed within the BCI data to be made use of, but further pre-processing and parameter exploration was needed to reach competitive classification rates.

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DO - 10.1007/978-3-642-17534-3_9

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Oliver G, Gedeon T. Brain computer interfaces: A recurrent neural network approach. In Neural Information Processing: Models and Applications - 17th International Conference, ICONIP 2010, Proceedings. PART 2 ed. 2010. p. 66-73. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-17534-3_9

Brain computer interfaces: A recurrent neural network approach

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