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 …
Recognition of human emotions using EEG signals: A review
Assessment of the cognitive functions and state of clinical subjects is an important aspect of
e-health care delivery, and in the development of novel human-machine interfaces. A …
e-health care delivery, and in the development of novel human-machine interfaces. A …
Taxonomy on EEG artifacts removal methods, issues, and healthcare applications
Electroencephalogram (EEG) signals are progressively growing data widely known as
biomedical big data, which is applied in biomedical and healthcare research. The …
biomedical big data, which is applied in biomedical and healthcare research. The …
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 …
[HTML][HTML] The PREP pipeline: standardized preprocessing for large-scale EEG analysis
The technology to collect brain imaging and physiological measures has become portable
and ubiquitous, opening the possibility of large-scale analysis of real-world human imaging …
and ubiquitous, opening the possibility of large-scale analysis of real-world human imaging …
EEG artifact removal—state-of-the-art and guidelines
JA Urigüen, B Garcia-Zapirain - Journal of neural engineering, 2015 - iopscience.iop.org
This paper presents an extensive review on the artifact removal algorithms used to remove
the main sources of interference encountered in the electroencephalogram (EEG) …
the main sources of interference encountered in the electroencephalogram (EEG) …
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 …
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 …
Automatic eyeblink and muscular artifact detection and removal from EEG signals using k-nearest neighbor classifier and long short-term memory networks
Electroencephalogram (EEG) is often corrupted with artifacts originating from sources such
as eyes and muscles. Hybrid artifact removal methods often require human intervention for …
as eyes and muscles. Hybrid artifact removal methods often require human intervention for …
Motion artifact removal techniques for wearable EEG and PPG sensor systems
Removal of motion artifacts is a critical challenge, especially in wearable
electroencephalography (EEG) and photoplethysmography (PPG) devices that are exposed …
electroencephalography (EEG) and photoplethysmography (PPG) devices that are exposed …