Prediction of P300 BCI Aptitude in Severe Motor Impairment

Sebastian Halder, Carolin Anne Ruf, Adrian Furdea, Emanuele Pasqualotto, Daniele De Massari, Linda van der Heiden, Martin Bogdan, Wolfgang Rosenstiel, Niels Birbaumer, Andrea Kübler, Tamara Matuz

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Abstract

Brain-computer interfaces (BCIs) provide a non-muscular communication channel for persons with severe motor impairments. Previous studies have shown that the aptitude with which a BCI can be controlled varies from person to person. A reliable predictor of performance could facilitate selection of a suitable BCI paradigm. Eleven severely motor impaired participants performed three sessions of a P300 BCI web browsing task. Before each session auditory oddball data were collected to predict the BCI aptitude of the participants exhibited in the current session. We found a strong relationship of early positive and negative potentials around 200 ms (elicited with the auditory oddball task) with performance. The amplitude of the P2 (r = -0.77) and of the N2 (r = -0.86) had the strongest correlations. Aptitude prediction using an auditory oddball was successful. The finding that the N2 amplitude is a stronger predictor of performance than P3 amplitude was reproduced after initially showing this effect with a healthy sample of BCI users. This will reduce strain on the end-users by minimizing the time needed to find suitable paradigms and inspire new approaches to improve performance.

Original languageEnglish
Article numbere76148
JournalPLoS One
Volume8
Issue number10
DOIs
Publication statusPublished - Oct 18 2013

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Brain-Computer Interfaces
Brain computer interface
Aptitude
brain
prediction
user interface
Task Performance and Analysis
browsing
animal communication
Communication

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Halder, S., Ruf, C. A., Furdea, A., Pasqualotto, E., De Massari, D., van der Heiden, L., ... Matuz, T. (2013). Prediction of P300 BCI Aptitude in Severe Motor Impairment. PLoS One, 8(10), [e76148]. https://doi.org/10.1371/journal.pone.0076148

Prediction of P300 BCI Aptitude in Severe Motor Impairment. / Halder, Sebastian; Ruf, Carolin Anne; Furdea, Adrian; Pasqualotto, Emanuele; De Massari, Daniele; van der Heiden, Linda; Bogdan, Martin; Rosenstiel, Wolfgang; Birbaumer, Niels; Kübler, Andrea; Matuz, Tamara.

In: PLoS One, Vol. 8, No. 10, e76148, 18.10.2013.

Research output: Contribution to journalArticle

Halder, S, Ruf, CA, Furdea, A, Pasqualotto, E, De Massari, D, van der Heiden, L, Bogdan, M, Rosenstiel, W, Birbaumer, N, Kübler, A & Matuz, T 2013, 'Prediction of P300 BCI Aptitude in Severe Motor Impairment', PLoS One, vol. 8, no. 10, e76148. https://doi.org/10.1371/journal.pone.0076148
Halder S, Ruf CA, Furdea A, Pasqualotto E, De Massari D, van der Heiden L et al. Prediction of P300 BCI Aptitude in Severe Motor Impairment. PLoS One. 2013 Oct 18;8(10). e76148. https://doi.org/10.1371/journal.pone.0076148
Halder, Sebastian ; Ruf, Carolin Anne ; Furdea, Adrian ; Pasqualotto, Emanuele ; De Massari, Daniele ; van der Heiden, Linda ; Bogdan, Martin ; Rosenstiel, Wolfgang ; Birbaumer, Niels ; Kübler, Andrea ; Matuz, Tamara. / Prediction of P300 BCI Aptitude in Severe Motor Impairment. In: PLoS One. 2013 ; Vol. 8, No. 10.
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