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Assessing the performance of an artifact detection/correction implemented in our Apps is a very important step. To have an idea how to do it, we sent the following message to the mailing list of different tools:

Dear XXX,

I performed an artifact detection/correction procedure and I am looking for a good way to visualize its results but also to assess its performance. I would imagine something akin to a script displaying a summary plot per participant showing all trials x channels and the scores of one or several measurements done before and after artifact detection/correction. More precisely, I would want to find a way to assess the quality of the artifact detection/correction or the quality of the corrected data, thanks to an index for instance.

Do you know a good application/function/script/favorite procedure that would allow me to do this? A paper reference would be of course most welcome!

Many thanks in advance,

Best

Message sent to

Date

Commentary

Answer

eeglablist@sccn.ucsd.edu

fieldtrip@science.ru.nl

I had to subscribe to the mailing list

  • see https://www.fieldtriptoolbox.org/workshop/madrid2019/tutorial_erp/#inspect-cleaned-data

  • “Alors pour les fonctions fieldtrip, la chose qui pourrait le plus se rapprocher de ce que tu me demandes serait un score de variance où tu pourrais définir un seuil (ex: 3x la variance) à partir duquel tu considères un trial/canal bruité. L'idée de partir du ft_rejectvisual en te permettant d'automatiser le quality check.”

  • “Pour ce qui est de la détection d'artefacts, si tu as des signaux BIOs (ex: EOG/EMG/ECG), tu pourrais lancer une ICA et partir sur un score de corrélation entre les composantes et ces signaux BIOs pour identifier automatiquement les composantes à retirer.”

https://neuroimage.usc.edu/forums/

Maybe ask directly Guio

mne_analysis@nmr.mgh.harvard.edu

Max has sent an email (not exactly the same as above), but maybe ask on the forum instead

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