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Removal of eye blink artifacts from EEG signal using morphological modeling and orthogonal projection

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Abstract

The presence of artifacts in the EEG signals can cause a misunderstanding of the sought neurophysiological phenomena. In particular, the eye blink artifacts frequently contaminate the EEG and deteriorate its quality. Unfortunately, removing this artifact can lose useful information. The most popular approach in this field uses the independent component analysis to decompose the signal into different independent components and then eliminate those that are related to the artifact. Despite its reputation, this approach is computationally intensive, requires an acquisition from large number of channels and can alter the original EEG signal. In this paper, we propose a new method for blink artifact reduction. Several reference signals representing the eye blink are created then used in an orthogonal projection in order to cancel the artifact. The results of experiments, using 54 datasets from 27 subjects, show that the proposed method significantly outperformed the standard ADJUST, MARA and SASICA methods in removing the artifacts while preserving the pure EEG signals.

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Acknowledgments

This work is carried out under the MOBIDOC scheme, funded by the European Union (EU) through the EMORI program and managed by the National Agency for the Promotion of Scientific Research (ANPR).

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Authors and Affiliations

  1. Advanced technologies for medicine and signals ‘ATMS’, ENIS, Sfax university, Sfax, Tunisia

    Omar Trigui, Mohamed Ghorbel & Ahmed Ben Hamida

  2. Department of neurology, Habib Bourguiba, university hospital, Sfax, Tunisia

    Sawsan Daoud, Mariem Dammak & Chokri Mhiri

  3. Neuroscience laboratory, Sfax university, LR-12-SP-19, Sfax, Tunisia

    Sawsan Daoud, Mariem Dammak & Chokri Mhiri

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  1. Omar Trigui
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  2. Sawsan Daoud
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  6. Ahmed Ben Hamida
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Correspondence to Omar Trigui.

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Trigui, O., Daoud, S., Ghorbel, M. et al. Removal of eye blink artifacts from EEG signal using morphological modeling and orthogonal projection. SIViP 16, 19–27 (2022). https://doi.org/10.1007/s11760-021-01947-w

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  • DOI: https://doi.org/10.1007/s11760-021-01947-w

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