Academic Journal
NEAR: An artifact removal pipeline for human newborn EEG data
| العنوان: | NEAR: An artifact removal pipeline for human newborn EEG data |
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| المؤلفون: | Kumaravel, Velu Prabhakar, Farella, Elisabetta, Parise, Eugenio, Buiatti, Marco |
| المساهمون: | Kumaravel, Velu Prabhakar, Farella, Elisabetta, Parise, Eugenio, Buiatti, Marco |
| سنة النشر: | 2022 |
| المجموعة: | Università degli Studi di Trento: CINECA IRIS |
| مصطلحات موضوعية: | EEG, Newborn, Infant, Artifact Removal, EEGLAB |
| الوصف: | Electroencephalography (EEG) is arising as a valuable method to investigate neurocognitive functions shortly after birth. However, obtaining high-quality EEG data from human newborn recordings is challenging. Compared to adults and older infants, datasets are typically much shorter due to newborns’ limited attentional span and much noisier due to non-stereotyped artifacts mainly caused by uncontrollable movements. We propose Newborn EEG Artifact Removal (NEAR), a pipeline for EEG artifact removal designed explicitly for human newborns. NEAR is based on two key steps: 1) A novel bad channel detection tool based on the Local Outlier Factor (LOF), a robust outlier detection algorithm; 2) A parameter calibration procedure for adapting to newborn EEG data the algorithm Artifacts Subspace Reconstruction (ASR), developed for artifact removal in mobile adult EEG. Tests on simulated data showed that NEAR outperforms existing methods in removing representative newborn non-stereotypical artifacts. NEAR was validated on two pediatric populations (newborns and 9-month-old infants) recorded with two different experimental designs (frequency-tagging and ERP). Results show that NEAR artifact removal successfully reproduces established EEG responses from noisy datasets, with a higher statistical significance than the one obtained by existing artifact removal methods. The EEGLAB-based NEAR pipeline is freely available at https://github.com/vpKumaravel/NEAR. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| Relation: | info:eu-repo/semantics/altIdentifier/pmid/35085870; info:eu-repo/semantics/altIdentifier/wos/WOS:000776070700003; volume:2022/54; firstpage:10106801; lastpage:10106814; numberofpages:14; journal:DEVELOPMENTAL COGNITIVE NEUROSCIENCE; http://hdl.handle.net/11572/328276; info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85123365939; https://www.sciencedirect.com/science/article/pii/S1878929322000123?via=ihub#! |
| DOI: | 10.1016/j.dcn.2022.101068 |
| الاتاحة: | http://hdl.handle.net/11572/328276 https://doi.org/10.1016/j.dcn.2022.101068 https://www.sciencedirect.com/science/article/pii/S1878929322000123?via=ihub#! |
| Rights: | info:eu-repo/semantics/openAccess |
| رقم الانضمام: | edsbas.8D69DAA2 |
| قاعدة البيانات: | BASE |
| DOI: | 10.1016/j.dcn.2022.101068 |
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