Common Spatial Pattern Patches: online evaluation on BCI-naive users.

Claudia Sannelli, Carmen Vidaurre, Klaus Robert Müller, Benjamin Blankertz

Research output: Contribution to journalArticle

Abstract

Brain-Computer Interfaces (BCI) based on the voluntary modulation of sensorimotor rhythms (SMRs) induced by motor imagery are very prominent because allow a continuous control of the external device. Nevertheless, the design of a SMR-based BCI system that provides every user with a reliable BCI control from the first session, i.e., without extensive training, is still a big challenge. Considerable advances in this direction have been made by the machine learning co-adaptive calibration approach, which combines online adaptation techniques with subject learning in order to offer the user a feedback from the beginning of the experiment. Recently, based on offline analyses, we proposed the novel Common Spatial Patterns Patches (CSPP) technique as a good candidate to improve the co-adaptive calibration. CSPP is an ensemble of localized spatial filters, each of them optimized on subject-specific data by CSP analysis. Here, the evaluation of CSPP in online operation is presented for the first time. Results on three BCI-naive participants show indeed promising results. All three users reach the threshold criterion of 70% accuracy within one session, even one candidate for whom the weak SMR at rest predicted deficient BCI control. Concurrent recordings of the SMR during a relax condition as well as the course of BCI performance indicate a clear learning effect.

Original languageEnglish
Pages (from-to)4744-4747
Number of pages4
JournalConference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
Publication statusPublished - 2012 Dec 1
Externally publishedYes

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ASJC Scopus subject areas

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

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