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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.