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Adaptive on-line classification for EEG-based brain computer interfaces with AAR parameters and band power estimates.

Publication ,  Journal Article
Vidaurre, C; Schlögl, A; Cabeza, R; Scherer, R; Pfurtscheller, G
Published in: Biomedizinische Technik. Biomedical engineering
November 2005

We present the result of on-line feedback Brain Computer Interface experiments using adaptive and non-adaptive feature extraction methods with an on-line adaptive classifier based on Quadratic Discriminant Analysis. Experiments were performed with 12 naïve subjects, feedback was provided from the first moment and no training sessions were needed. Experiments run in three different days with each subject. Six of them received feedback with Adaptive Autoregressive parameters and the rest with logarithmic Band Power estimates. The study was done using single trial analysis of each of the sessions and the value of the Error Rate and the Mutual Information of the classification were used to discuss the results. Finally, it was shown that even subjects starting with a low performance were able to control the system in a few hours: and contrary to previous results no differences between AAR and BP estimates were found.

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Published In

Biomedizinische Technik. Biomedical engineering

DOI

EISSN

1862-278X

ISSN

0013-5585

Publication Date

November 2005

Volume

50

Issue

11

Start / End Page

350 / 354

Related Subject Headings

  • User-Computer Interface
  • Sensitivity and Specificity
  • Reproducibility of Results
  • Pattern Recognition, Automated
  • Humans
  • Evoked Potentials
  • Electroencephalography
  • Communication Aids for Disabled
  • Brain
  • Biomedical Engineering
 

Citation

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Vidaurre, C., Schlögl, A., Cabeza, R., Scherer, R., & Pfurtscheller, G. (2005). Adaptive on-line classification for EEG-based brain computer interfaces with AAR parameters and band power estimates. Biomedizinische Technik. Biomedical Engineering, 50(11), 350–354. https://doi.org/10.1515/bmt.2005.049
Vidaurre, C., A. Schlögl, R. Cabeza, R. Scherer, and G. Pfurtscheller. “Adaptive on-line classification for EEG-based brain computer interfaces with AAR parameters and band power estimates.Biomedizinische Technik. Biomedical Engineering 50, no. 11 (November 2005): 350–54. https://doi.org/10.1515/bmt.2005.049.
Vidaurre C, Schlögl A, Cabeza R, Scherer R, Pfurtscheller G. Adaptive on-line classification for EEG-based brain computer interfaces with AAR parameters and band power estimates. Biomedizinische Technik Biomedical engineering. 2005 Nov;50(11):350–4.
Vidaurre, C., et al. “Adaptive on-line classification for EEG-based brain computer interfaces with AAR parameters and band power estimates.Biomedizinische Technik. Biomedical Engineering, vol. 50, no. 11, Nov. 2005, pp. 350–54. Epmc, doi:10.1515/bmt.2005.049.
Vidaurre C, Schlögl A, Cabeza R, Scherer R, Pfurtscheller G. Adaptive on-line classification for EEG-based brain computer interfaces with AAR parameters and band power estimates. Biomedizinische Technik Biomedical engineering. 2005 Nov;50(11):350–354.
Journal cover image

Published In

Biomedizinische Technik. Biomedical engineering

DOI

EISSN

1862-278X

ISSN

0013-5585

Publication Date

November 2005

Volume

50

Issue

11

Start / End Page

350 / 354

Related Subject Headings

  • User-Computer Interface
  • Sensitivity and Specificity
  • Reproducibility of Results
  • Pattern Recognition, Automated
  • Humans
  • Evoked Potentials
  • Electroencephalography
  • Communication Aids for Disabled
  • Brain
  • Biomedical Engineering