Methods for artifact detection and removal from scalp EEG: A review

MK Islam, A Rastegarnia, Z Yang - Neurophysiologie Clinique/Clinical …, 2016 - Elsevier
Electroencephalography (EEG) is the most popular brain activity recording technique used
in wide range of applications. One of the commonly faced problems in EEG recordings is the …

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 …

Measuring workers' emotional state during construction tasks using wearable EEG

S Hwang, H Jebelli, B Choi, M Choi… - Journal of Construction …, 2018 - ascelibrary.org
Construction workers' emotional states (eg, pleasure, displeasure, excitement, and
relaxation) are known as a critical factor that affect their performance (eg, safety, health, and …

Density-weighted support vector machines for binary class imbalance learning

BB Hazarika, D Gupta - Neural Computing and Applications, 2021 - Springer
In real-world binary classification problems, the entirety of samples belonging to each class
varies. These types of problems where the majority class is notably bigger than the minority …

[HTML][HTML] Filtering techniques for channel selection in motor imagery EEG applications: a survey

MZ Baig, N Aslam, HPH Shum - Artificial intelligence review, 2020 - Springer
Brain computer interface (BCI) systems are used in a wide range of applications such as
communication, neuro-prosthetic and environmental control for disabled persons using …

EEG signal-processing framework to obtain high-quality brain waves from an off-the-shelf wearable EEG device

H Jebelli, S Hwang, SH Lee - Journal of Computing in Civil …, 2018 - ascelibrary.org
Investigating brain waves collected by an electroencephalogram (EEG) can be useful in
understanding human psychosocial conditions such as stress, emotional exhaustion …

Automatic artifact rejection from multichannel scalp EEG by wavelet ICA

N Mammone, F La Foresta… - IEEE Sensors Journal, 2011 - ieeexplore.ieee.org
Electroencephalographic (EEG) recordings are often contaminated by artifacts, ie, signals
with noncerebral origin that might mimic some cognitive or pathologic activity, this way …

Real-time epileptic seizure prediction using AR models and support vector machines

L Chisci, A Mavino, G Perferi… - IEEE Transactions …, 2010 - ieeexplore.ieee.org
This paper addresses the prediction of epileptic seizures from the online analysis of EEG
data. This problem is of paramount importance for the realization of monitoring/control units …

Sleep scoring using artificial neural networks

M Ronzhina, O Janoušek, J Kolářová, M Nováková… - Sleep medicine …, 2012 - Elsevier
Rapid development of computer technologies leads to the intensive automation of many
different processes traditionally performed by human experts. One of the spheres …

Removal of muscle artifacts from the EEG: A review and recommendations

X Chen, X Xu, A Liu, S Lee, X Chen… - IEEE Sensors …, 2019 - ieeexplore.ieee.org
Electroencephalography (EEG) has been widely used for studying brain function. As cortical
signals recorded by the EEG are very weak, they are often obscured by motion artifacts and …