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EEG and fMRI Artifact Detection Techniques: A Survey of Recent Developments

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Abstract

The evolution of different techniques for exploring cerebral activity and the development of signal processing and analysis methods have enabled a better understanding of the dynamic cerebral mechanisms in favor of fine diagnosis and characterization of certain diseases such as dementia and epilepsy. Integration of functional magnetic resonance imaging (fMRI) with electroencephalography (EEG) has offered the possibility of understanding new insights into neuroscientific studies because of the higher temporal and spatial measurements of brain activity when compared with the use of each technique separately. However, the experimental limitations of fMRI/EEG are mainly the numerous artifacts, mainly due to switching of magnetic field gradients and cardiac activity. To provide a comprehensive overview of this research area, a systematic mapping study has been conducted. This mapping study aims to identify the topics studied within the artifacts’ detection in EEG and fMRI data, as well as examine the adopted research methodologies, identify the gaps in the current research and point to directions for future research.

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Author notes

  1. Bassem Bouaziz, Ahmed Maalel and Faiez Gargouri contributed equally to this work.

Authors and Affiliations

  1. Multimedia InfoRmation Systems and Advanced Computing Laboratory (MIRACL), Faculty of Economics and Management of Sfax, University of Sfax, 3021, Sfax, Tunisia

    Rahma Mili & Faiez Gargouri

  2. Multimedia InfoRmation Systems and Advanced Computing Laboratory (MIRACL), Higher Institute of Computer and Multimedia of Sfax, 3021, Sfax, Tunisia

    Bassem Bouaziz & Faiez Gargouri

  3. RIADI Laboratory, National School of Computer Sciences, University of Manouba, 2010, Manouba, Tunisia

    Ahmed Maalel

  4. Higher Institute of Applied Sciences and Technology, University of Sousse, 4003, Sousse , Tunisia

    Ahmed Maalel

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This article is part of the topical collection “Recent Trends on AI for HealthCare” guest edited by Lydia Bouzar-Benlabiod.

Appendix

Appendix

See Table 10.

Table 10 The selected primary studies
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Mili, R., Bouaziz, B., Maalel, A. et al. EEG and fMRI Artifact Detection Techniques: A Survey of Recent Developments. SN COMPUT. SCI. 4, 528 (2023). https://doi.org/10.1007/s42979-023-01959-y

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  • DOI: https://doi.org/10.1007/s42979-023-01959-y

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