[HTML][HTML] International Federation of Clinical Neurophysiology (IFCN)–EEG research workgroup: Recommendations on frequency and topographic analysis of resting …

C Babiloni, RJ Barry, E Başar, KJ Blinowska… - Clinical …, 2020 - Elsevier
Abstract In 1999, the International Federation of Clinical Neurophysiology (IFCN) published
“IFCN Guidelines for topographic and frequency analysis of EEGs and EPs”(Nuwer et al …

EEG/MEG source imaging: methods, challenges, and open issues

K Wendel, O Väisänen, J Malmivuo… - Computational …, 2009 - Wiley Online Library
We present the four key areas of research—preprocessing, the volume conductor, the
forward problem, and the inverse problem—that affect the performance of EEG and MEG …

Pitfalls of high-pass filtering for detecting epileptic oscillations: a technical note on “false” ripples

CG Bénar, L Chauvière, F Bartolomei… - Clinical …, 2010 - Elsevier
OBJECTIVES: To analyze interictal High frequency oscillations (HFOs) as observed in the
medial temporal lobe of epileptic patients and animals (ripples, 80–200Hz and fast ripples …

Time-frequency mixed-norm estimates: Sparse M/EEG imaging with non-stationary source activations

A Gramfort, D Strohmeier, J Haueisen, MS Hämäläinen… - NeuroImage, 2013 - Elsevier
Magnetoencephalography (MEG) and electroencephalography (EEG) allow functional brain
imaging with high temporal resolution. While solving the inverse problem independently at …

Sparsity enables estimation of both subcortical and cortical activity from MEG and EEG

P Krishnaswamy, G Obregon-Henao… - Proceedings of the …, 2017 - National Acad Sciences
Subcortical structures play a critical role in brain function. However, options for assessing
electrophysiological activity in these structures are limited. Electromagnetic fields generated …

Multichannel matching pursuit for seismic trace decomposition

Y Wang - Geophysics, 2010 - library.seg.org
The technique of matching pursuit can adaptively decompose a seismic trace into a series of
wavelets. However, the solution is not unique and is also strongly affected by data noise …

[BOOK][B] Practical biomedical signal analysis using MATLAB®

KJ Blinowska, J Żygierewicz - 2021 - taylorfrancis.com
Covering the latest cutting-edge techniques in biomedical signal processing while
presenting a coherent treatment of various signal processing methods and applications, this …

Decreased sleep spindle density in patients with idiopathic REM sleep behavior disorder and patients with Parkinson's disease

JAE Christensen, J Kempfner, M Zoetmulder… - Clinical …, 2014 - Elsevier
Objective To determine whether sleep spindles (SS) are potentially a biomarker for
Parkinson's disease (PD). Methods Fifteen PD patients with REM sleep behavior disorder …

Solving the EEG inverse problem based on space–time–frequency structured sparsity constraints

S Castaño-Candamil, J Höhne, JD Martínez-Vargas… - NeuroImage, 2015 - Elsevier
We introduce STOUT (spatio-temporal unifying tomography), a novel method for the source
analysis of electroencephalograpic (EEG) recordings, which is based on a physiologically …

A removal of eye movement and blink artifacts from EEG data using morphological component analysis

B Singh, H Wagatsuma - Computational and mathematical …, 2017 - Wiley Online Library
EEG signals contain a large amount of ocular artifacts with different time‐frequency
properties mixing together in EEGs of interest. The artifact removal has been substantially …