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Journal article · Conference paper

Investigating effects of different artefact types on motor imagery BCI

From

Department of Applied Mathematics and Computer Science, Technical University of Denmark1

Cognitive Systems, Department of Applied Mathematics and Computer Science, Technical University of Denmark2

Technische Universität Berlin3

Fraunhofer-Gesellschaft4

Artefacts in recordings of the electroencephalogram (EEG) are a common problem in Brain-Computer Interfaces (BCIs). Artefacts make it difficult to calibrate from training sessions, resulting in low test performance, or lead to artificially high performance when unintentionally used for BCI control. We investigate different artefacts' effects on motor-imagery based BCI relying on Common Spatial Patterns (CSP).

Data stem from an 80-subject BCI study. We use the recently developed classifier IC_MARC to classify independent components of EEG data into neural and five classes of artefacts. We find that muscle, but not ocular, artefacts adversely affect BCI performance when all 119 EEG channels are used. Artefacts have little influence when using 48 centrally located EEG channels in a configuration previously found to be optimal.

Language: English
Publisher: IEEE
Year: 2015
Pages: 1942-1945
Proceedings: 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Series: I E E E Engineering in Medicine and Biology Society. Conference Proceedings
ISBN: 1424492696 , 142449270X , 1424492718 , 9781424492695 , 9781424492701 and 9781424492718
ISSN: 26940604 , 1557170x and 23757477
Types: Journal article and Conference paper
DOI: 10.1109/EMBC.2015.7318764

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