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Investigating effects of different artefact types on motor imagery BCI

: Frølich, L.; Winkler, I.; Müller, K.-R.; Samek, W.


Cerutti, S. ; Institute of Electrical and Electronics Engineers -IEEE-; IEEE Engineering in Medicine and Biology Society -EMBS-:
37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015. Vol.3 : Milan, Italy, 25 - 29 August 2015
Piscataway, NJ: IEEE, 2015
ISBN: 978-1-4244-9269-5
ISBN: 978-1-4244-9270-1
Engineering in Medicine and Biology Society (EMBC Annual International Conference) <37, 2015, Milan>
Fraunhofer HHI ()

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.