An automated magnetoencephalographic data cleaning algorithm. Issue 14 (26th October 2019) - Sorriso, Antonietta; Sorrentino, Pierpaolo; Rucco, Rosaria; Mandolesi, Laura; Ferraioli, Giampaolo; Franceschini, Stefano; Ambrosanio, Michele; Baselice, Fabio
Abstract: The problem of cleaning magnetoencephalographic data is addressed in this manuscript. At present, several denoising procedures have been proposed in the literature, nevertheless their adoption is limited due to the difficulty in implementing and properly tuning the algorithms. Therefore, as of today, the gold standard remains manual cleaning. We propose an approach developed with the aim of automating each step of the manual cleaning. Its peculiarities are the ease of implementation and using and the remarkable reproducibility of the results. Interestingly, the algorithm has been designed to imitate the reasoning behind the manual procedure, carried out by trained experts. Our statistical analysis shows that no significant differences can be found between the two approaches.