Table of Contents
Journal of Medical Engineering
Volume 2016 (2016), Article ID 9614323, 17 pages
http://dx.doi.org/10.1155/2016/9614323
Research Article

Gradient Artefact Correction and Evaluation of the EEG Recorded Simultaneously with fMRI Data Using Optimised Moving-Average

1Department of Electrical Engineering, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, Netherlands
2Philips Research Laboratories Eindhoven, Professor Holstlaan 4, 5656 AE Eindhoven, Netherlands

Received 23 March 2016; Accepted 22 May 2016

Academic Editor: Norio Iriguchi

Copyright © 2016 José L. Ferreira et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Over the past years, coregistered EEG-fMRI has emerged as a powerful tool for neurocognitive research and correlated studies, mainly because of the possibility of integrating the high temporal resolution of the EEG with the high spatial resolution of fMRI. However, additional work remains to be done in order to improve the quality of the EEG signal recorded simultaneously with fMRI data, in particular regarding the occurrence of the gradient artefact. We devised and presented in this paper a novel approach for gradient artefact correction based upon optimised moving-average filtering (OMA). OMA makes use of the iterative application of a moving-average filter, which allows estimation and cancellation of the gradient artefact by integration. Additionally, OMA is capable of performing the attenuation of the periodic artefact activity without accurate information about MRI triggers. By using our proposed approach, it is possible to achieve a better balance than the slice-average subtraction as performed by the established AAS method, regarding EEG signal preservation together with effective suppression of the gradient artefact. Since the stochastic nature of the EEG signal complicates the assessment of EEG preservation after application of the gradient artefact correction, we also propose a simple and effective method to account for it.