Title :
FORCe: Fully Online and Automated Artifact Removal for Brain-Computer Interfacing
Author :
Daly, Ian ; Scherer, Reinhold ; Billinger, Martin ; Muller-Putz, Gernot
Author_Institution :
Institute for Knowledge Discovery, Laboratory of Brain-Computer Interfaces, Graz University of Technology, Graz, Austria
Abstract :
A fully automated and online artifact removal method for the electroencephalogram (EEG) is developed for use in brain-computer interfacing (BCI). The method (FORCe) is based upon a novel combination of wavelet decomposition, independent component analysis, and thresholding. FORCe is able to operate on a small channel set during online EEG acquisition and does not require additional signals (e.g., electrooculogram signals). Evaluation of FORCe is performed offline on EEG recorded from 13 BCI particpants with cerebral palsy (CP) and online with three healthy participants. The method outperforms the state-of the-art automated artifact removal methods Lagged Auto-Mutual Information Clustering (LAMIC) and Fully Automated Statistical Thresholding for EEG artifact Rejection (FASTER), and is able to remove a wide range of artifact types including blink, electromyogram (EMG), and electrooculogram (EOG) artifacts.
Keywords :
Approximation methods; Electroencephalography; Electromyography; Force; Integrated circuits; Scalp; Standards; Automated online artifact removal; brain-computer interface (BCI); electroencephalogram (EEG); independent component analysis; wavelets;
Journal_Title :
Neural Systems and Rehabilitation Engineering, IEEE Transactions on
DOI :
10.1109/TNSRE.2014.2346621