Asynchronous Brain Computer Interface using Hidden Semi-Markov Models

Gareth Oliver; Peter Sunehag; Tom Gedeon

doi:10.1109/EMBC.2012.6346528

Asynchronous Brain Computer Interface using Hidden Semi-Markov Models

Gareth Oliver, Peter Sunehag, Tom Gedeon

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

Abstract

Ideal Brain Computer Interfaces need to perform asynchronously and at real time. We propose Hidden Semi-Markov Models(HSMM) to better segment and classify EEG data. The proposed HSMM method was tested against a simple windowed method on standard datasets. We found that our HSMM outperformed the simple windowed method. Furthermore, due to the computational demands of the algorithm, we adapted the HSMM algorithm to an online setting and demonstrate that this faster version of the algorithm can run in real time.

Original language	English
Title of host publication	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Editors	Michael C. K. Khoo; Gert Cauwenberghs; James Weiland
Place of Publication	Piscataway, New Jersey
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2728-2731
Edition	Peer Reviewed
ISBN (Print)	9781457717871
DOIs	https://doi.org/10.1109/EMBC.2012.6346528
Publication status	Published - 2012
Event	IEEE International Conference of the Engineering in Medicine and Biology Society (EMBS 2012) - San Diego, USA, United States Duration: 1 Jan 2012 → … http://dx.doi.org/10.1109/EMBC.2012.6347194

Conference

Conference	IEEE International Conference of the Engineering in Medicine and Biology Society (EMBS 2012)
Country/Territory	United States
Period	1/01/12 → …
Other	August 28-September 1 2012
Internet address	http://dx.doi.org/10.1109/EMBC.2012.6347194

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10.1109/EMBC.2012.6346528

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Oliver, G., Sunehag, P., & Gedeon, T. (2012). Asynchronous Brain Computer Interface using Hidden Semi-Markov Models. In M. C. K. K. G. C. J. W. (Ed.), Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (Peer Reviewed ed., pp. 2728-2731). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2012.6346528

Oliver, Gareth ; Sunehag, Peter ; Gedeon, Tom. / Asynchronous Brain Computer Interface using Hidden Semi-Markov Models. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. editor / Michael C. K. Khoo; Gert Cauwenberghs; James Weiland. Peer Reviewed. ed. Piscataway, New Jersey : Institute of Electrical and Electronics Engineers Inc., 2012. pp. 2728-2731

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title = "Asynchronous Brain Computer Interface using Hidden Semi-Markov Models",

abstract = "Ideal Brain Computer Interfaces need to perform asynchronously and at real time. We propose Hidden Semi-Markov Models(HSMM) to better segment and classify EEG data. The proposed HSMM method was tested against a simple windowed method on standard datasets. We found that our HSMM outperformed the simple windowed method. Furthermore, due to the computational demands of the algorithm, we adapted the HSMM algorithm to an online setting and demonstrate that this faster version of the algorithm can run in real time.",

author = "Gareth Oliver and Peter Sunehag and Tom Gedeon",

year = "2012",

doi = "10.1109/EMBC.2012.6346528",

language = "English",

isbn = "9781457717871",

pages = "2728--2731",

editor = "{Michael C. K. Khoo; Gert Cauwenberghs; James Weiland}",

booktitle = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

edition = "Peer Reviewed",

note = "IEEE International Conference of the Engineering in Medicine and Biology Society (EMBS 2012) ; Conference date: 01-01-2012",

url = "http://dx.doi.org/10.1109/EMBC.2012.6347194",

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Oliver, G, Sunehag, P & Gedeon, T 2012, Asynchronous Brain Computer Interface using Hidden Semi-Markov Models. in MCKKGCJW (ed.), Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. Peer Reviewed edn, Institute of Electrical and Electronics Engineers Inc., Piscataway, New Jersey, pp. 2728-2731, IEEE International Conference of the Engineering in Medicine and Biology Society (EMBS 2012), United States, 1/01/12. https://doi.org/10.1109/EMBC.2012.6346528

Asynchronous Brain Computer Interface using Hidden Semi-Markov Models. / Oliver, Gareth; Sunehag, Peter; Gedeon, Tom.
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. ed. / Michael C. K. Khoo; Gert Cauwenberghs; James Weiland. Peer Reviewed. ed. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers Inc., 2012. p. 2728-2731.

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

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AB - Ideal Brain Computer Interfaces need to perform asynchronously and at real time. We propose Hidden Semi-Markov Models(HSMM) to better segment and classify EEG data. The proposed HSMM method was tested against a simple windowed method on standard datasets. We found that our HSMM outperformed the simple windowed method. Furthermore, due to the computational demands of the algorithm, we adapted the HSMM algorithm to an online setting and demonstrate that this faster version of the algorithm can run in real time.

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Oliver G, Sunehag P, Gedeon T. Asynchronous Brain Computer Interface using Hidden Semi-Markov Models. In MCKKGCJW, editor, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. Peer Reviewed ed. Piscataway, New Jersey: Institute of Electrical and Electronics Engineers Inc. 2012. p. 2728-2731 doi: 10.1109/EMBC.2012.6346528

Asynchronous Brain Computer Interface using Hidden Semi-Markov Models

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