Robust common spatial patterns based on Bhattacharyya distance and Gamma divergence

Stephanie Brandl, Klaus Robert Muller, Wojciech Samek

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

9 Citations (Scopus)

Abstract

The computation of task-related spatial filters is a prerequisite for a successful application of motor imagery-based Brain-Computer Interfaces (BCI). However, in the presence of artifacts, e.g., resulting from eye movements or muscular activity, standard methods such as Common Spatial Patterns (CSP) perform poorly. Recently, a divergence-based spatial filter computation framework has been proposed which enables significantly more robust computation with respect to artifacts by using Beta divergence. In this paper we integrate two additional divergence measures, namely Bhattacharyya distance and Gamma divergence, into the divergence-based CSP framework and evaluate their robustness using simulations and data set IVa from BCI Competition III.

Original languageEnglish
Title of host publication3rd International Winter Conference on Brain-Computer Interface, BCI 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479974948
DOIs
Publication statusPublished - 2015 Mar 30
Event2015 3rd International Winter Conference on Brain-Computer Interface, BCI 2015 - Gangwon-Do, Korea, Republic of
Duration: 2015 Jan 122015 Jan 14

Publication series

Name3rd International Winter Conference on Brain-Computer Interface, BCI 2015

Other

Other2015 3rd International Winter Conference on Brain-Computer Interface, BCI 2015
Country/TerritoryKorea, Republic of
CityGangwon-Do
Period15/1/1215/1/14

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Cognitive Neuroscience
  • Sensory Systems

Fingerprint

Dive into the research topics of 'Robust common spatial patterns based on Bhattacharyya distance and Gamma divergence'. Together they form a unique fingerprint.

Cite this