Various dimension reduction techniques for high dimensional data analysis: a review
In the era of healthcare, and its related research fields, the dimensionality problem of high
dimensional data is a massive challenge as it contains a huge number of variables forming …
dimensional data is a massive challenge as it contains a huge number of variables forming …
A survey of signal processing algorithms in brain–computer interfaces based on electrical brain signals
Brain–computer interfaces (BCIs) aim at providing a non-muscular channel for sending
commands to the external world using the electroencephalographic activity or other …
commands to the external world using the electroencephalographic activity or other …
Whale optimization approaches for wrapper feature selection
M Mafarja, S Mirjalili - Applied Soft Computing, 2018 - Elsevier
Classification accuracy highly dependents on the nature of the features in a dataset which
may contain irrelevant or redundant data. The main aim of feature selection is to eliminate …
may contain irrelevant or redundant data. The main aim of feature selection is to eliminate …
A tensor-based frequency features combination method for brain–computer interfaces
Y Pei, Z Luo, H Zhao, D Xu, W Li, Y Yan… - … on Neural Systems …, 2021 - ieeexplore.ieee.org
With the development of the brain-computer interface (BCI) community, motor imagery-
based BCI system using electroencephalogram (EEG) has attracted increasing attention …
based BCI system using electroencephalogram (EEG) has attracted increasing attention …
Electroencephalographic motor imagery brain connectivity analysis for BCI: a review
M Hamedi, SH Salleh, AM Noor - Neural computation, 2016 - ieeexplore.ieee.org
Recent research has reached a consensus on the feasibility of motor imagery brain-
computer interface (MI-BCI) for different applications, especially in stroke rehabilitation. Most …
computer interface (MI-BCI) for different applications, especially in stroke rehabilitation. Most …
EMG and EOG artifacts in brain computer interface systems: A survey
It is widely accepted in the brain computer interface (BCI) research community that
neurological phenomena are the only source of control in any BCI system. Artifacts are …
neurological phenomena are the only source of control in any BCI system. Artifacts are …
In silico prediction of blood–brain barrier permeability of compounds by machine learning and resampling methods
The blood–brain barrier (BBB) as a part of absorption protects the central nervous system by
separating the brain tissue from the bloodstream. In recent years, BBB permeability has …
separating the brain tissue from the bloodstream. In recent years, BBB permeability has …
Comparative analysis of spectral approaches to feature extraction for EEG-based motor imagery classification
The quantification of the spectral content of electroencephalogram (EEG) recordings has a
substantial role in clinical and scientific applications. It is of particular relevance in the …
substantial role in clinical and scientific applications. It is of particular relevance in the …
[HTML][HTML] A novel framework for prognostic factors identification of malignant mesothelioma through association rule mining
Malignant mesothelioma (MM) is a rare cancer type arising from mesothelial cells. The
current clinical diagnosis is based on contrast-enhanced computed tomography, magnetic …
current clinical diagnosis is based on contrast-enhanced computed tomography, magnetic …
Support vector machines to detect physiological patterns for EEG and EMG-based human–computer interaction: a review
Support vector machines (SVMs) are widely used classifiers for detecting physiological
patterns in human–computer interaction (HCI). Their success is due to their versatility …
patterns in human–computer interaction (HCI). Their success is due to their versatility …