Review of brain–computer interface based on steady‐state visual evoked potential

S Liu, D Zhang, Z Liu, M Liu, Z Ming… - Brain Science …, 2022 - journals.sagepub.com
The brain–computer interface (BCI) technology has received lots of attention in the field of
scientific research because it can help disabled people improve their quality of life. Steady …

Multiscale image fusion using complex extensions of EMD

D Looney, DP Mandic - IEEE Transactions on Signal …, 2009 - ieeexplore.ieee.org
Empirical mode decomposition (EMD) is a fully data driven technique for decomposing
signals into their natural scale components. However the problem of uniqueness, caused by …

Comparison of EMD, DWT and WPD for the localization of epileptogenic foci using random forest classifier

A Subasi, S Jukic, J Kevric - Measurement, 2019 - Elsevier
Localization of epileptogenic foci is an essential phase in surgical treatment planning using
the earliest time detection of the seizure onset in the recordings of electroencephalogram …

[PDF][PDF] Non-negative matrix factorization, a new tool for feature extraction: theory and applications

I Buciu - … Journal of Computers, Communications and Control, 2008 - Citeseer
Despite its relative novelty, non-negative matrix factorization (NMF) method knew a huge
interest from the scientific community, due to its simplicity and intuitive decomposition. Plenty …

Source-space ICA for EEG source separation, localization, and time-course reconstruction

Y Jonmohamadi, G Poudel, C Innes, R Jones - NeuroImage, 2014 - Elsevier
We propose source-space independent component analysis (ICA) for separation,
tomography, and time-course reconstruction of EEG and MEG source signals. Source-space …

Identifying metastatic ability of prostate cancer cell lines using native fluorescence spectroscopy and machine learning methods

J Xue, Y Pu, J Smith, X Gao, C Wang, B Wu - Scientific Reports, 2021 - nature.com
Metastasis is the leading cause of mortalities in cancer patients due to the spreading of
cancer cells to various organs. Detecting cancer and identifying its metastatic potential at the …

Epileptic seizure detection using empirical mode decomposition

AK Tafreshi, AM Nasrabadi… - 2008 IEEE International …, 2008 - ieeexplore.ieee.org
In this paper, we attempt to analyze the performance of the Empirical Mode Decomposition
(EMD) for discriminating epileptic seizure data from the normal data. The Empirical Mode …

Selection of an efficient feature space for EEG-based mental task discrimination

S Noshadi, V Abootalebi, MT Sadeghi… - Biocybernetics and …, 2014 - Elsevier
The aim of this paper is to contribute toward exploring an optimal feature space for
discriminating mental tasks. Empirical mode decomposition (EMD) algorithm seems useful …

Feature selection algorithm for evoked EEG signal due to RGB colors

ET Alharbi, S Rasheed… - 2016 9th International …, 2016 - ieeexplore.ieee.org
In this paper, a single trial classification is introduced for the Electroencephalography (EEG)
signals evoked by RGB colors. The effectiveness of a single trial classification is an …

Measuring phase synchrony using complex extensions of EMD

D Looney, C Park, P Kidmose… - 2009 IEEE/SP 15th …, 2009 - ieeexplore.ieee.org
A framework for the robust assessment of phase synchrony between multichannel
observations is introduced. This is achieved by using empirical mode decomposition (EMD) …