Background: EEG signals are often contaminated with artefacts, particularly with large signals generated by eye blinks. Deletion of artefact can lose valuable data. Current methods of removing the eye blink component to leave residual EEG, such as blind source component removal, require multichannel recording, are computationally intensive, and can alter the original EEG signal.
New method: Here we describe a novel single-channel method using a model based on the ballistic physiological components of the eye blink. This removes the blink component, leaving uncontaminated EEG largely unchanged. Processing time allows its use in real-time applications such as neurofeedback training.
Results: Blink removal had a success rate of over 90% recovered variance of original EEG when removing synthesised eye blink components. Fronto-lateral sites were poorer (∼80%) than most other sites (92–96%), with poor fronto-polar results (67%).
Comparisons with existing methods: When compared with three popular independent component analysis (ICA) methods, our method was only slightly (1%) better at frontal midline sites but significantly (>20%) better at lateral sites with an overall advantage of ~10%.
Conclusions: With few recording channels and real-time processing, our method shows clear advantages over ICA for removing eye blinks. It should be particularly suited for use in portable brain-computerinterfaces and in neurofeedback training.