title: Single Versus Multiple Events Error Potential Detection in a BCI-Controlled Car Game With Continuous and Discrete Feedback.
abstract: OBJECTIVE
  This work aimed to find and evaluate a new method for detecting errors in continuous brain-computer interface (BCI) applications. Instead of classifying errors on a single-trial basis, the new method was based on multiple events (MEs) analysis to increase the accuracy of error detection.
  
  
  METHODS
  In a BCI-driven car game, based on motor imagery (MI), discrete events were triggered whenever subjects collided with coins and/or barriers. Coins counted as correct events, whereas barriers were errors. This new method, termed ME method, combined and averaged the classification results of single events (SEs) and determined the correctness of MI trials, which consisted of event sequences instead of SEs. The benefit of this method was evaluated in an offline simulation. In an online experiment, the new method was used to detect erroneous MI trials. Such MI trials were discarded and could be repeated by the users.
  
  
  RESULTS
  We found that, even with low SE error potential (ErrP) detection rates, feasible accuracies can be achieved when combining MEs to distinguish erroneous from correct MI trials. Online, all subjects reached higher scores with error detection than without, at the cost of longer times needed for completing the game.
  
  
  CONCLUSIONS
  Findings suggest that ErrP detection may become a reliable tool for monitoring continuous states in BCI applications when combining MEs.
  
  
  CONCLUSIONS
  This paper demonstrates a novel technique for detecting errors in online continuous BCI applications, which yields promising results even with low single-trial detection rates.
authors.forename: Alex
authors.initials: A
authors.lastname: Kreilinger
authors.forename: Hannah
authors.initials: H
authors.lastname: Hiebel
authors.forename: Gernot R
authors.initials: GR
authors.lastname: Müller-Putz
mesh_terms: D000328:Adult; D062207:Brain-Computer Interfaces / Q000592:standards*; D004569:Electroencephalography / Q000592:standards*; D005246:Feedback; D005260:Female; D006801:Humans; D007092:Imagination; D008297:Male; D012815:Signal Processing, Computer-Assisted; D018910:Video Games; D055815:Young Adult