Open Access
SHS Web Conf.
Volume 139, 2022
The 4th ETLTC International Conference on ICT Integration in Technical Education (ETLTC2022)
Article Number 03029
Number of page(s) 5
Section Topics in Computer Science
Published online 13 May 2022
  1. M.K. Islam, A. Rastegarnia, Z. Yang “Methods for artifact detection and removal from scalp EEG: a review”, Neurophysiol. Clin./Clin. Neurophysiol., 46 (4) (2016), pp. 287-305, 10.1016/j.neucli.2016.07.002 [CrossRef] [Google Scholar]
  2. L.J. Gabard-Durnam, A.S. Mendez Leal, C.L. Wilkinson, A.R. Levin The Harvard Automated Processing Pipeline for Electroencephalography (HAPPE): standardized processing software for developmental and high-artifact data. Front. Neurosci., 12 (2018), p. 12, 10.3389/fnins.2018.00097 [Google Scholar]
  3. R. Debnath, G.A. Buzzell, S. Morales, M.E. Bowers, S.C. Leach, N.A. Fox The Maryland analysis of developmental EEG (MADE) pipeline Psychophysiology, 57 (6) (2020), Article e13580, [Google Scholar]
  4. Velu Prabhakar, Kumaravelab, Elisabetta Farellaa, Eugenio Pariseb, Marco Buiattib, “NEAR: An artifact removal pipeline for human newborn EEG data”, [Google Scholar]
  5. Bigdely-Shamlo et al., 2015 N. Bigdely-Shamlo, T. Mullen, C. Kothe, K.-M. Su, K.A. Robbins, “The PREP pipeline: standardized preprocessing for large-scale EEG analysis” Front. Neuroinform., 9 (June) (2015), pp. 1-20, 10.3389/fninf.2015.00016 [Google Scholar]
  6. A. Mognon, J. Jovicich, L. Bruzzone, M. Buiatti “ADJUST: an automatic EEG artifact detector based on the joint use of spatial and temporal features” Psychophysiology, 48 (2) (2011), pp. 229-240, 10.1111/j.1469-8986.2010.01061.x [CrossRef] [Google Scholar]
  7. H. Nolan, R. Whelan, R.B. Reilly, “FASTER: fully automated statistical thresholding for EEG artifact rejection” J. Neurosci. Methods, 192 (1) (2010), pp. 152-162, 10.1016/j.jneumeth.2010.07.015 [CrossRef] [Google Scholar]
  8. A. De Cheveigné, L.C. Parra "Joint decorrelation, a versatile tool for multichannel data analysis" NeuroImage, 98 (2014), pp. 487-505, 10.1016/j.neuroimage.2014.05.068 [CrossRef] [Google Scholar]
  9. A. de Cheveigné, D. Arzounian, “Robust detrending, rereferencing, outlier detection, and inpainting for multichannel data”, NeuroImage, 172 (2018), pp. 903-912, 10.1016/j.neuroimage.2018.01.035. [CrossRef] [Google Scholar]
  10. M. Eisermann, A. Kaminska, M.-L. Moutard, C. Soufflet, P. Plouin, “Normal EEG in childhood: from neonates to adolescents”, Neurophysiol. Clin./Clin. Neurophysiol., 43 (1) (2013), pp. 35-65, 10.1016/j.neucli.2012.09.091 [CrossRef] [Google Scholar]
  11. Winkler, I., Debener, S., Müller, K., Tangermann, M., 2015. On the influence of high-pass filtering on ICA-based artifact reduction in EEG-ERP. In: Proceedings of the 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 4101–5. [Google Scholar]
  12. M. Eisermann, A. Kaminska, M.-L. Moutard, C. Soufflet, P. Plouin " Normal EEG in childhood: from neonates to adolescents", Neurophysiol. Clin./Clin. Neurophysiol., 43 (1) (2013), pp. 35-65, 10.1016/j.neucli.2012.09.091 [CrossRef] [Google Scholar]
  13. E. Kushnerenko, R. Ceponienė, P. Balan, V. Fellman, R. Näätänen, “Maturation of the auditory change detection response in infants: a longitudinal ERP study” Neuroreport, 13 (15) (2002), pp. 3-8 [Google Scholar]
  14. P.J. Marshall, Y. Bar-Haim, N.A. Fox, “Development of the EEG from 5 months to 4 years of age”, Clin. Neurophysiol., 113 (8) (2002), pp. 1199-1208 [CrossRef] [Google Scholar]
  15. C.A. Nelson, C.S. Monk, “The use of event-related potentials in the study of cognitive development”, Handbook of Developmental Cognitive Neuroscience, MIT Press [Google Scholar]

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