EEG-Based Brain-Computer Interaction: Improved Accuracy by Automatic Single-Trial Error Detection

Brain-computer interfaces (BCIs), as any other interaction modality based on physiological signals and body channels (e.g., muscular activity, speech and gestures), are prone to errors in the recognition of subject’s intent. An elegant approach to improve the accuracy of BCIs consists in a verification procedure directly based on the presence of error-related potentials (ErrP) in the EEG recorded right after the occurrence of an error. Six healthy volunteer subjects with no prior BCI experience participated in a new human-robot interaction experiment where they were asked to mentally move a cursor towards a target that can be reached within a few steps using motor imagination. This experiment confirms the previously reported presence of a new kind of ErrP. These “Interaction ErrP” exhibit a first sharp negative peak followed by a positive peak and a second broader negative peak (∼290, ∼350 and ∼470 ms after the feedback, respectively). But in order to exploit these ErrP...

• Type: Conference
• Year: 2007
• Where: NIPS
• Authors: Pierre W. Ferrez, José del R. Millán
• Keywords: Information Technology, Negative Peak, NIPS 2007, Prior Bci Experience, Sharp Negative Peak