A Convolutional Neural Network for Artifacts Detection in EEG Data

Improved Manual Annotation of EEG Signals through Convolutional Neural Network Guidance

“…Automation is mainly achieved through channel referencing ( Schlögl et al, 2007 ), by applying various thresholding mechanisms ( Castellanos and Makarov, 2006 ; Gao et al, 2010 ; Nolan et al, 2010 ; Mognon et al, 2011 ; Akhtar et al, 2012 ; Islam and Tcheslavski, 2016 ; Jas et al, 2017 ), or using feature extraction followed by classification with conventional machine-learning algorithms such as support vector machines ( Shoker et al, 2005 ; Halder et al, 2007 ; Shao et al, 2009 ; Gabard-Durnam et al, 2018 ; Sai et al, 2018 ). In recent years, deep-learning algorithms have gained popularity to address EEG signal denoising ( Wang et al, 2018 ; B Yang et al, 2018 ; Craik et al, 2019 ; Pion-Tonachini et al, 2019 ; Roy et al, 2019 ; Sun et al, 2020 ; Boudaya et al, 2022 ; Jurczak et al, 2022 ; Liu et al, 2022 ), providing a more flexible solution than traditional methods by taking advantage of end-to-end learning, i.e., using a single model to act as both feature extractor and classifier. For example, because of hierarchical feature learning, convolutional neural networks (CNNs; LeCun et al, 1989 , 1998 , 2010 , 2015 ) can recognize complex patterns from minimally preprocessed data.…”

Robin’s Viewer: Using Deep-Learning Predictions to Assist EEG Annotation

“…Given the need of neurologists to analyze large amounts of data, efforts have increased towards using various machine learning techniques for handling artifacts in EEG data (Shoker et al 2005; Shao et al 2008; Barua and Begum, 2014; Pardede et al, 2015; Radüntz et al, 2015; Yang et al, 2016, 2018; Sai et al, 2017; Wang et al, 2017; Craik et al, 2019; Roy et al, 2019; Sun et al, 2020; Boudaya et al, 2022; Jurczak et al, 2022; Liu et al, 2022; Diachenko, M., Houtman, S. J., Juarez-Martinez, E. L., Ramautar, J. R., Weiler, R., Mansvelder, H. D., Bruining, H., Bloem, P., & Linkenkaer-Hansen K. (2022). Improved manual annotation of EEG signals through convolutional neural network guidance.…”

“…Examples of machine learning techniques applied in artifact detection are support vector machines (SVMs) (Shoker et al 2005; Shao et al 2008; Bartels et al, 2010; Sai et al, 2017), k-nearest neighbor classifiers (k-NN) (Gao et al, 2010), and independent component analysis (ICA) (Barua and Begum, 2014; Radüntz et al, 2015). Recently, efforts have focused on developing deep-learning solutions for artifact detection (Pardede et al, 2015; Craik et al, 2019; Roy et al, 2019; Sun et al, 2020; Boudaya et al, 2022; Jurczak et al, 2022; Liu et al, 2022; Diachenko, M., Houtman, S. J., Juarez-Martinez, E. L., Ramautar, J. R., Weiler, R., Mansvelder, H. D., Bruining, H., Bloem, P., & Linkenkaer-Hansen K. (2022). Improved manual annotation of EEG signals through convolutional neural network guidance.…”