Abstract
For data preprocessing and artefact removal in an ERP experiment we were confronted with the question how blink artefacts can be detected reliably, even in the absence of usable electrooculogram (EOG) data. We propose an objective and quantitative method for the automatic detection of eyeblink artefacts from raw data using extreme value statistics, with a p-value acting as a threshold parameter. For testing the method, we used 29 channel electroencephalogram recordings of 55 healthy subjects. A total 7,700 s of EEG were analysed. The proposed method was found to detect blink artefacts reliably, showing that extreme value statistics can be employed to detect blink artefacts, even in the absence of EOG recordings.
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Notes
This is the case for a uniform distribution, for example, but not for an amplifier running into saturation.
The pROC-software issued a warning about possible unexpected results with different specificity levels, but we see currently no method to evaluate their correctness as the manual offers only a short explanation but no solution to the problem.
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Acknowledgments
We would like to thank Mr. Benjamin Würzer for helping with data recording and visually screening the EEG data for artefacts. All computations for this article were performed with the following free open source software packages: GNU-Octave (Eaton et al. 2008), pROC (Robin et al. 2011), and GNU-R (R Development Core Team 2011).
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Klein, A., Skrandies, W. A Reliable Statistical Method to Detect Eyeblink-Artefacts from Electroencephalogram Data Only. Brain Topogr 26, 558–568 (2013). https://doi.org/10.1007/s10548-013-0281-2
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DOI: https://doi.org/10.1007/s10548-013-0281-2