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 …
VME-DWT: An efficient algorithm for detection and elimination of eye blink from short segments of single EEG channel
Objective: Recent advances in development of low-cost single-channel
electroencephalography (EEG) headbands have opened new possibilities for applications …
electroencephalography (EEG) headbands have opened new possibilities for applications …
Formulation of the challenges in brain-computer interfaces as optimization problems—a review
Electroencephalogram (EEG) is one of the common modalities of monitoring the mental
activities. Owing to the non-invasive availability of this system, its applicability has seen …
activities. Owing to the non-invasive availability of this system, its applicability has seen …
A segmentation-denoising network for artifact removal from single-channel EEG
As an important neurorecording technique, electroencephalography (EEG) is often
contaminated by various artifacts, which obstructs subsequent analysis. In recent years …
contaminated by various artifacts, which obstructs subsequent analysis. In recent years …
One-dimensional convolutional neural network architecture for classification of mental tasks from electroencephalogram
Cognitive/mental task classification using single/limited channel (s) electroencephalogram
(EEG) signals in real-time play an important role in designing portable brain-computer …
(EEG) signals in real-time play an important role in designing portable brain-computer …
A GAN guided parallel CNN and transformer network for EEG denoising
Electroencephalography (EEG) signals are often contaminated with various physiological
artifacts, seriously affecting the quality of subsequent analysis. Therefore, removing artifacts …
artifacts, seriously affecting the quality of subsequent analysis. Therefore, removing artifacts …
Wavelet based waveform distortion measures for assessment of denoised EEG quality with reference to noise-free EEG signal
An objective distortion measure is very crucial to accurately quantify the distortion introduced
in the electroencephalogram (EEG) signal during the denoising process. Most of the existing …
in the electroencephalogram (EEG) signal during the denoising process. Most of the existing …
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 …
Contextual imputation with missing sequence of EEG signals using generative adversarial networks
W Lee, J Lee, Y Kim - IEEE Access, 2021 - ieeexplore.ieee.org
Missing values are very prevalent in real world; they are caused by various reasons such as
user mistakes or device failures. They often cause critical problems especially in medical …
user mistakes or device failures. They often cause critical problems especially in medical …