Removal of artifacts from EEG signals: a review
Electroencephalogram (EEG) plays an important role in identifying brain activity and
behavior. However, the recorded electrical activity always be contaminated with artifacts and …
behavior. However, the recorded electrical activity always be contaminated with artifacts and …
[HTML][HTML] Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions
Removing the bias and variance of multicentre data has always been a challenge in large
scale digital healthcare studies, which requires the ability to integrate clinical features …
scale digital healthcare studies, which requires the ability to integrate clinical features …
A Machine Learning‐Based Big EEG Data Artifact Detection and Wavelet‐Based Removal: An Empirical Approach
The electroencephalogram (EEG) signals are a big data which are frequently corrupted by
motion artifacts. As human neural diseases, diagnosis and analysis need a robust …
motion artifacts. As human neural diseases, diagnosis and analysis need a robust …
Review of challenges associated with the EEG artifact removal methods
Electroencephalography (EEG), as a non-invasive modality, enables the representation of
the underlying neuronal activities as electrical signals with high temporal resolution. In …
the underlying neuronal activities as electrical signals with high temporal resolution. In …
Trends in EEG-BCI for daily-life: Requirements for artifact removal
J Minguillon, MA Lopez-Gordo, F Pelayo - Biomedical Signal Processing …, 2017 - Elsevier
Since the discovery of the EEG principles by Berger in the 20's, procedures for artifact
removal have been essential in its pre-processing. In literature, diverse approaches based …
removal have been essential in its pre-processing. In literature, diverse approaches based …
Artifact removal in physiological signals—Practices and possibilities
KT Sweeney, TE Ward… - IEEE transactions on …, 2012 - ieeexplore.ieee.org
The combination of reducing birth rate and increasing life expectancy continues to drive the
demographic shift toward an aging population. This, in turn, places an ever-increasing …
demographic shift toward an aging population. This, in turn, places an ever-increasing …
Unsupervised eye blink artifact denoising of EEG data with modified multiscale sample entropy, kurtosis, and wavelet-ICA
R Mahajan, BI Morshed - IEEE journal of Biomedical and …, 2014 - ieeexplore.ieee.org
Brain activities commonly recorded using the electroencephalogram (EEG) are
contaminated with ocular artifacts. These activities can be suppressed using a robust …
contaminated with ocular artifacts. These activities can be suppressed using a robust …
Design of hydrogel-based wearable EEG electrodes for medical applications
The electroencephalogram (EEG) is considered to be a promising method for studying brain
disorders. Because of its non-invasive nature, subjects take a lower risk compared to some …
disorders. Because of its non-invasive nature, subjects take a lower risk compared to some …
An evaluation of mental workload with frontal EEG
Using a wireless single channel EEG device, we investigated the feasibility of using short-
term frontal EEG as a means to evaluate the dynamic changes of mental workload. Frontal …
term frontal EEG as a means to evaluate the dynamic changes of mental workload. Frontal …
Automatic sleep stage classification: From classical machine learning methods to deep learning
RN Sekkal, F Bereksi-Reguig… - … Signal Processing and …, 2022 - Elsevier
Background and objectives The classification of sleep stages is a preliminary exam that
contributes to the diagnosis of possible sleep disorders. However, it is a tedious and time …
contributes to the diagnosis of possible sleep disorders. However, it is a tedious and time …