A simple generative model applied to motor-imagery brain-computer interfacing

Andrew Geronimo, Steven Schiff, Mst Kamrunnahar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

In this study, a generative model is developed in order to translate neural activity into predictable device commands for brain-computer interface (BCI) applications. Generative approaches to BCI translation differ from widely-used discriminative approaches because they develop a model of brain activity dependent on the mental state of the user. Preliminary results indicate that two of three subjects were able to control the system at a level (<70% accurate) that makes it a viable option for practical use. The accuracy rate of the generative model is compared to the accuracy rate calculated offline using a linear discriminant approach. The advantages of such a system are discussed, and the ongoing opportunities for paradigm improvement are outlined.

Original languageEnglish (US)
Title of host publication2011 5th International IEEE/EMBS Conference on Neural Engineering, NER 2011
Pages400-403
Number of pages4
DOIs
StatePublished - Jul 20 2011
Event2011 5th International IEEE/EMBS Conference on Neural Engineering, NER 2011 - Cancun, Mexico
Duration: Apr 27 2011May 1 2011

Publication series

Name2011 5th International IEEE/EMBS Conference on Neural Engineering, NER 2011

Other

Other2011 5th International IEEE/EMBS Conference on Neural Engineering, NER 2011
CountryMexico
CityCancun
Period4/27/115/1/11

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All Science Journal Classification (ASJC) codes

  • Neuroscience(all)

Cite this

Geronimo, A., Schiff, S., & Kamrunnahar, M. (2011). A simple generative model applied to motor-imagery brain-computer interfacing. In 2011 5th International IEEE/EMBS Conference on Neural Engineering, NER 2011 (pp. 400-403). [5910571] (2011 5th International IEEE/EMBS Conference on Neural Engineering, NER 2011). https://doi.org/10.1109/NER.2011.5910571