Ocular artifact elimination from electroencephalography signals: A systematic review
Electroencephalography (EEG) is the signal of intrigue that has immense application in the
clinical diagnosis of various neurological, psychiatric, psychological, psychophysiological …
clinical diagnosis of various neurological, psychiatric, psychological, psychophysiological …
Unsupervised eye blink artifact detection from EEG with Gaussian mixture model
J Cao, L Chen, D Hu, F Dong, T Jiang… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
Eye blink is one of the most common artifacts in electroencephalogram (EEG) and
significantly affects the performance of the EEG related applications, such as epilepsy …
significantly affects the performance of the EEG related applications, such as epilepsy …
EEG-based motor imagery channel selection and classification using hybrid optimization and two-tier deep learning
Brain–computer interface (BCI) technology holds promise for individuals with profound
motor impairments, offering the potential for communication and control. Motor imagery (MI) …
motor impairments, offering the potential for communication and control. Motor imagery (MI) …
Design of an automatic hybrid system for removal of eye-blink artifacts from EEG recordings
S Çınar - Biomedical Signal Processing and Control, 2021 - Elsevier
Electroencephalography (EEG) signals are frequently used in several areas, such as
diagnosis of diseases and BCI applications. It is important to remove noise sources for …
diagnosis of diseases and BCI applications. It is important to remove noise sources for …
Automated CCA-MWF algorithm for unsupervised identification and removal of EOG artifacts from EEG
M Miao, W Hu, B Xu, J Zhang… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
Affective brain computer interface (ABCI) enables machines to perceive, understand,
express and respond to people's emotions. Therefore, it is expected to play an important role …
express and respond to people's emotions. Therefore, it is expected to play an important role …
Automatic EEG eyeblink artefact identification and removal technique using independent component analysis in combination with support vector machines and …
This study proposes a novel combination of independent component analysis (ICA) in
conjunction with support vector machine (SVM) and denoising autoencoder (DA), for the first …
conjunction with support vector machine (SVM) and denoising autoencoder (DA), for the first …
AOAR: an automatic ocular artifact removal approach for multi-channel electroencephalogram data based on non-negative matrix factorization and empirical mode …
Objective. Electroencephalogram (EEG) signals suffer inevitable interference from artifacts
during the acquisition process. These artifacts make the analysis and interpretation of EEG …
during the acquisition process. These artifacts make the analysis and interpretation of EEG …
Ocular artifacts elimination from multivariate EEG signal using frequency-spatial filtering
The electroencephalogram (EEG) signals record electrical activities generated by the brain
cells and are used as a state-of-the-art diagnosis tool for various neural disorders. However …
cells and are used as a state-of-the-art diagnosis tool for various neural disorders. However …
A fast and scalable framework for automated artifact recognition from EEG signals represented in scalp topographies of independent components
Background and objectives Electroencephalography (EEG) measures the electrical brain
activity in real-time by using sensors placed on the scalp. Artifacts due to eye movements …
activity in real-time by using sensors placed on the scalp. Artifacts due to eye movements …
Feature fusion for improving performance of motor imagery brain-computer interface system
A brain-computer interface (BCI) is a system that makes communication between an external
device and the brain based on the brain's neural activity. This communication is conducted …
device and the brain based on the brain's neural activity. This communication is conducted …