Brain-computer interfacing in discriminative and stationary subspaces

Wojciech Samek, Klaus Muller, Motoaki Kawanabe, Carmen Vidaurre

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

Abstract

The non-stationary nature of neurophysiological measurements, e.g. EEG, makes classification of motion intentions a demanding task. Variations in the underlying brain processes often lead to significant and unexpected changes in the feature distribution resulting in decreased classification accuracy in Brain Computer Interfacing (BCI). Several methods were developed to tackle this problem by either adapting to these changes or extracting features that are invariant. Recently, a method called Stationary Subspace Analysis (SSA) was proposed and applied to BCI data. It diminishes the influence of non-stationary changes as learning and classification is performed in a stationary subspace of the data which can be extracted by SSA. In this paper we extend this method in two ways. First we propose a variant of SSA that allows to extract stationary subspaces from labeled data without disregarding class-related variations or treating class-differences as non-stationarities. Second we propose a discriminant variant of SSA that trades-off stationarity and discriminativity, thus it allows to extract stationary subspaces without losing relevant information. We show that learning in a discriminative and stationary subspace is advantageous for BCI application and outperforms the standard SSA method.

Original languageEnglish
Title of host publicationProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Pages2873-2876
Number of pages4
DOIs
Publication statusPublished - 2012 Dec 14
Externally publishedYes
Event34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 - San Diego, CA, United States
Duration: 2012 Aug 282012 Sep 1

Other

Other34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012
CountryUnited States
CitySan Diego, CA
Period12/8/2812/9/1

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

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  • Cite this

    Samek, W., Muller, K., Kawanabe, M., & Vidaurre, C. (2012). Brain-computer interfacing in discriminative and stationary subspaces. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (pp. 2873-2876). [6346563] https://doi.org/10.1109/EMBC.2012.6346563