EEG-based Endogenous Online Co-Adaptive Brain-Computer Interfaces: Strategy for Success?

Reinhold Scherer, Josef Faller, Paul Sajda, Carmen Vidaurre

Publikation: KonferenzbeitragPaperForschungBegutachtung

Abstract

A Brain-Computer Interface (BCI) translates patterns of brain signals such as the electroencephalogram (EEG) into messages for communication and control. In the case of endogenous systems the reliable detection of induced patterns is more challenging than the detection of the more stable and stereotypical evoked responses. In the former case specific mental activities such as motor imagery are used to encode different messages. In the latter case users have to attend to sensory stimuli to evoke a characteristic response. Indeed, a large number of users who try to control endogenous BCIs do not reach sufficient level of accuracy. This fact is also known as BCI “inefficiency” or “illiteracy”. In this paper we discuss and make some conjectures, based on our knowledge and experience in BCI, on whether or not online co-adaptation of human and machine can be the solution to overcome this challenge. We point out some ingredients that might be necessary for the system to be reliable and allow the users to attain sufficient control.
Originalspracheenglisch
Seiten299-304
DOIs
PublikationsstatusVeröffentlicht - 2019
Veranstaltung2018 The 10th Computer Science and Electronic Engineering (CEEC) - University of Essex, Colchester, Großbritannien / Vereinigtes Königreich
Dauer: 19 Sep 201821 Sep 2018
http://ceec.uk/

Konferenz

Konferenz2018 The 10th Computer Science and Electronic Engineering (CEEC)
KurztitelCEEC
LandGroßbritannien / Vereinigtes Königreich
OrtColchester
Zeitraum19/09/1821/09/18
Internetadresse

Fingerprint

Brain computer interface
Electroencephalography
Brain
Communication

Fields of Expertise

  • Human- & Biotechnology

Dies zitieren

Scherer, R., Faller, J., Sajda, P., & Vidaurre, C. (2019). EEG-based Endogenous Online Co-Adaptive Brain-Computer Interfaces: Strategy for Success?. 299-304. Beitrag in 2018 The 10th Computer Science and Electronic Engineering (CEEC), Colchester, Großbritannien / Vereinigtes Königreich. https://doi.org/10.1109/CEEC.2018.8674198

EEG-based Endogenous Online Co-Adaptive Brain-Computer Interfaces: Strategy for Success? / Scherer, Reinhold; Faller, Josef; Sajda, Paul; Vidaurre, Carmen.

2019. 299-304 Beitrag in 2018 The 10th Computer Science and Electronic Engineering (CEEC), Colchester, Großbritannien / Vereinigtes Königreich.

Publikation: KonferenzbeitragPaperForschungBegutachtung

Scherer, R, Faller, J, Sajda, P & Vidaurre, C 2019, 'EEG-based Endogenous Online Co-Adaptive Brain-Computer Interfaces: Strategy for Success?' Beitrag in, Colchester, Großbritannien / Vereinigtes Königreich, 19/09/18 - 21/09/18, S. 299-304. https://doi.org/10.1109/CEEC.2018.8674198
Scherer R, Faller J, Sajda P, Vidaurre C. EEG-based Endogenous Online Co-Adaptive Brain-Computer Interfaces: Strategy for Success?. 2019. Beitrag in 2018 The 10th Computer Science and Electronic Engineering (CEEC), Colchester, Großbritannien / Vereinigtes Königreich. https://doi.org/10.1109/CEEC.2018.8674198
Scherer, Reinhold ; Faller, Josef ; Sajda, Paul ; Vidaurre, Carmen. / EEG-based Endogenous Online Co-Adaptive Brain-Computer Interfaces: Strategy for Success?. Beitrag in 2018 The 10th Computer Science and Electronic Engineering (CEEC), Colchester, Großbritannien / Vereinigtes Königreich.
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