Empirical Inference

Multitask Learning for Brain-Computer Interfaces

2010

Conference Paper

ei


Brain-computer interfaces (BCIs) are limited in their applicability in everyday settings by the current necessity to record subjectspecific calibration data prior to actual use of the BCI for communication. In this paper, we utilize the framework of multitask learning to construct a BCI that can be used without any subject-specific calibration process. We discuss how this out-of-the-box BCI can be further improved in a computationally efficient manner as subject-specific data becomes available. The feasibility of the approach is demonstrated on two sets of experimental EEG data recorded during a standard two-class motor imagery paradigm from a total of 19 healthy subjects. Specifically, we show that satisfactory classification results can be achieved with zero training data, and combining prior recordings with subjectspecific calibration data substantially outperforms using subject-specific data only. Our results further show that transfer between recordings under slightly different experimental setups is feasible.

Author(s): Alamgir, M. and Grosse-Wentrup, M. and Altun, Y.
Book Title: JMLR Workshop and Conference Proceedings Volume 9: AISTATS 2010
Journal: Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2010)
Pages: 17-24
Year: 2010
Month: May
Day: 0
Editors: Teh, Y.W. , M. Titterington
Publisher: JMLR

Department(s): Empirical Inference
Bibtex Type: Conference Paper (inproceedings)

Event Name: Thirteenth International Conference on Artificial Intelligence and Statistics
Event Place: Chia Laguna Resort, Italy

Address: Cambridge, MA, USA
Digital: 0
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

Links: PDF
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BibTex

@inproceedings{6504,
  title = {Multitask Learning for Brain-Computer Interfaces},
  author = {Alamgir, M. and Grosse-Wentrup, M. and Altun, Y.},
  journal = {Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2010)},
  booktitle = {JMLR Workshop and Conference Proceedings Volume 9: AISTATS 2010},
  pages = {17-24},
  editors = {Teh, Y.W. , M. Titterington},
  publisher = {JMLR},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  address = {Cambridge, MA, USA},
  month = may,
  year = {2010},
  doi = {},
  month_numeric = {5}
}