A Survey of EEG and Machine Learning based methods for Neural Rehabilitation
One approach to therapy and training for the restoration of damaged muscles and motor
systems is rehabilitation. EEG-assisted Brain-Computer Interface (BCI) may assist in …
systems is rehabilitation. EEG-assisted Brain-Computer Interface (BCI) may assist in …
A GAN guided parallel CNN and transformer network for EEG denoising
Electroencephalography (EEG) signals are often contaminated with various physiological
artifacts, seriously affecting the quality of subsequent analysis. Therefore, removing artifacts …
artifacts, seriously affecting the quality of subsequent analysis. Therefore, removing artifacts …
[HTML][HTML] Design of intelligent neuro-supervised networks for brain electrical activity rhythms of Parkinson's disease model
The objective of this paper is to present a novel design of intelligent neuro-supervised
networks (INSNs) in order to study the dynamics of a mathematical model for Parkinson's …
networks (INSNs) in order to study the dynamics of a mathematical model for Parkinson's …
CIS feature selection based dynamic ensemble selection model for human stress detection from EEG signals
Stress has an impact not only on a person's physical health but also on his or her ability to
perform at work, passion, and attitude in day-to-day life. It is one of the most difficult …
perform at work, passion, and attitude in day-to-day life. It is one of the most difficult …
[HTML][HTML] Improved EEG-based emotion recognition through information enhancement in connectivity feature map
Electroencephalography (EEG), despite its inherited complexity, is a preferable brain signal
for automatic human emotion recognition (ER), which is a challenging machine learning task …
for automatic human emotion recognition (ER), which is a challenging machine learning task …
Autonomous detection of myocarditis based on the fusion of improved quantum genetic algorithm and adaptive differential evolution optimization back propagation …
L Wu, S Guo, L Han, X Song, Z Zhao… - … Information Science and …, 2023 - Springer
Myocarditis is cardiac damage caused by a viral infection. Its result often leads to a variety of
arrhythmias. However, rapid and reliable identification of myocarditis has a great impact on …
arrhythmias. However, rapid and reliable identification of myocarditis has a great impact on …
A Comprehensive Survey of EEG Preprocessing Methods for Cognitive Load Assessment
K Kyriaki, D Koukopoulos, CA Fidas - IEEE Access, 2024 - ieeexplore.ieee.org
Preprocessing electroencephalographic (EEG) signals during computer-mediated Cognitive
Load tasks is crucial in Human-Computer Interaction (HCI). This process significantly …
Load tasks is crucial in Human-Computer Interaction (HCI). This process significantly …
Efficient novel network and index for alcoholism detection from EEGs
Background Alcoholism is a catastrophic condition that causes brain damage as well as
neurological, social, and behavioral difficulties. Limitations This illness is often assessed …
neurological, social, and behavioral difficulties. Limitations This illness is often assessed …
[HTML][HTML] Resting-state EEG connectivity at high-frequency bands and attentional performance dysfunction in stabilized schizophrenia patients
Background and Objectives: Attentional dysfunction has long been viewed as one of the
fundamental underlying cognitive deficits in schizophrenia. There is an urgent need to …
fundamental underlying cognitive deficits in schizophrenia. There is an urgent need to …
Measuring Connectivity in Linear Multivariate Processes with Penalized Regression Techniques
The evaluation of time and frequency domain measures of coupling and causality relies on
the parametric representation of linear multivariate processes. The study of temporal …
the parametric representation of linear multivariate processes. The study of temporal …