Shenghuan Zhang1, Julia McIntosh2, Shabah M Shadli2, Phoebe S-H Neo3, Zhiyi Huang1, Neil McNaughton4. 1. Dept. Computer Science, University of Otago, Dunedin, New Zealand. 2. Dept. of Psychology, University of Otago, Dunedin, New Zealand. 3. Dept. Computer Science, University of Otago, Dunedin, New Zealand; Dept. of Psychology, University of Otago, Dunedin, New Zealand. 4. Dept. of Psychology, University of Otago, Dunedin, New Zealand. Electronic address: nmcn@psy.otago.ac.nz.
Abstract
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-computer-interfaces and in neurofeedback training.
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-computer-interfaces and in neurofeedback training.
Authors: Shabah Mohammad Shadli; Tame Kawe; Daniel Martin; Neil McNaughton; Shona Neehoff; Paul Glue Journal: Int J Neuropsychopharmacol Date: 2018-08-01 Impact factor: 5.176
Authors: George Al Boustani; Lennart Jakob Konstantin Weiß; Hongwei Li; Svea Marie Meyer; Lukas Hiendlmeier; Philipp Rinklin; Bjoern Menze; Werner Hemmert; Bernhard Wolfrum Journal: Front Hum Neurosci Date: 2022-06-02 Impact factor: 3.473