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 …

Electroencephalography in the diagnosis of genetic generalized epilepsy syndromes

U Seneviratne, MJ Cook, WJ D'Souza - Frontiers in neurology, 2017 - frontiersin.org
Genetic generalized epilepsy (GGE) consists of several syndromes diagnosed and
classified on the basis of clinical features and electroencephalographic (EEG) abnormalities …

[图书][B] Niedermeyer's electroencephalography: basic principles, clinical applications, and related fields

E Niedermeyer - 2011 - books.google.com
" This edition has several new features, reflective of the changes that have occurred in our
field over the last 5 years since the fifth edition. More and more, the field of digital recording …

A novel end-to-end 1D-ResCNN model to remove artifact from EEG signals

W Sun, Y Su, X Wu, X Wu - Neurocomputing, 2020 - Elsevier
Electroencephalography (EEG) signals are an important tool in the field of clinical medicine,
brain research and the study of neurological diseases. EEG is very susceptible to a variety of …

Wavelet domain optimized Savitzky–Golay filter for the removal of motion artifacts from EEG recordings

P Gajbhiye, N Mingchinda, W Chen… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Motion artifact is observed in electroencephalogram (EEG) signals during the acquisition.
The elimination of this type of artifact using various signal processing approaches is …

A dynamic center and multi threshold point based stable feature extraction network for driver fatigue detection utilizing EEG signals

T Tuncer, S Dogan, F Ertam, A Subasi - Cognitive neurodynamics, 2021 - Springer
Driver fatigue is the one of the main reasons of the traffic accidents. The human brain is a
complex structure, whose function can be evaluated with electroencephalogram (EEG) …

Classifying electroencephalogram signals using an innovative and effective machine learning method based on chaotic elephant herding optimum

A Alqahtani, N Alqahtani, AA Alsulami, S Ojo… - Expert …, 2023 - Wiley Online Library
The field of electroencephalography (EEG) has made significant contributions to our
understanding of the brain, our understanding of neurological diseases, and our ability to …

Using a standalone ear-EEG device for focal-onset seizure detection

MG Joyner, SH Hsu, S Martin, J Dwyer, DF Chen… - Bioelectronic …, 2024 - Springer
Background Seizure detection is challenging outside the clinical environment due to the lack
of comfortable, reliable, and practical long-term neurophysiological monitoring devices. We …

Ambulatory EEG usefulness in epilepsy management

TF Hasan, WO Tatum IV - Journal of Clinical Neurophysiology, 2021 - journals.lww.com
Long-term video-EEG monitoring has been the gold standard for diagnosis of epileptic and
nonepileptic events. Medication changes, safety, and a lack of recording EEG in one's …

Water-soluble adhesive for stable long-term ambulatory EEG recordings

ES Nurse, K Marlow, PJ Hennessy… - Clinical …, 2022 - Elsevier
Objective Conventional methods used to adhere EEG electrodes are often uncomfortable.
Here, we present a polymer-based water-soluble EEG adhesive that can be maintained for …