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Supervised EEG Ocular Artefact Correction Through Eye-Tracking

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Advances in Neurotechnology, Electronics and Informatics

Part of the book series: Biosystems & Biorobotics ((BIOSYSROB,volume 12))

Abstract

Electroencephalography (EEG) is a widely used brain signal recording technique with many uses. The information conveyed in these recordings is a useful tool in the diagnosis of some diseases and disturbances, basic science, as well as in the development of non-invasive Brain-Machine Interfaces (BMI). However, the electrical recording setup comes with two major downsides, a. poor signal-to-noise ratio and b. the vulnerability to any external and internal noise sources. One of the main sources of artefacts is eye movements due to the electric dipole between the cornea and the retina. We have previously proposed that monitoring eye-movements provides a complementary signal for BMIs. Here we propose a novel technique to remove eye-related artefacts from the EEG recordings. We coupled Eye Tracking with EEG allowing us to independently measure when ocular artefact events occur through the eye tracker and thus clean them up in a targeted “supervised” manner instead of using a “blind” artefact clean up correction technique. Three standard methods of artefact correction were applied in an event-driven, supervised manner: 1. Independent Components Analysis (ICA), 2. Wiener Filter and 3. Wavelet Decomposition and compared to “blind” unsupervised ICA clean up. These are standard artefact correction approaches implemented in many toolboxes and experimental EEG systems and could easily be applied by their users in an event-driven manner. Already the qualitative inspection of the clean up traces shows that the simple targeted artefact event-driven clean up outperforms the traditional “blind” clean up approaches. We conclude that this justifies the small extra effort of performing simultaneous eye tracking with any EEG recording to enable simple, but targeted, automatic artefact removal that preserves more of the original signal.

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Acknowledgments

We acknowledge NEUROTECHNIX 2014 (Rome, Italy), where this work was originally contributed for their conference proceedings [36], and we are grateful that the paper was now selected for this publication format.

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Authors and Affiliations

  1. Brain and Behaviour Lab, Department of Bioengineering, Imperial College London, Exhibition Road, London, UK

    P. Rente Lourenço, W. W. Abbott & A. Aldo Faisal

  2. Brain and Behaviour Lab, Department of Computing, Imperial College London, Exhibition Road, London, SW7 2AZ, UK

    A. Aldo Faisal

Authors
  1. P. Rente Lourenço
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  2. W. W. Abbott
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  3. A. Aldo Faisal
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Corresponding author

Correspondence to A. Aldo Faisal .

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Editors and Affiliations

  1. Faculdade de Medicina, Universidade de Lisboa, Lisboa, Portugal

    Ana Rita Londral

  2. Faculty of Engineering, Universidade Católica Portuguesa, Lisbon, Portugal

    Pedro Encarnação

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Lourenço, P.R., Abbott, W.W., Faisal, A.A. (2016). Supervised EEG Ocular Artefact Correction Through Eye-Tracking. In: Londral, A., Encarnação, P. (eds) Advances in Neurotechnology, Electronics and Informatics. Biosystems & Biorobotics, vol 12. Springer, Cham. https://doi.org/10.1007/978-3-319-26242-0_7

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  • DOI: https://doi.org/10.1007/978-3-319-26242-0_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26240-6

  • Online ISBN: 978-3-319-26242-0

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