EEG artifact removal—state-of-the-art and guidelines
JA Urigüen, B Garcia-Zapirain - Journal of neural engineering, 2015 - iopscience.iop.org
This paper presents an extensive review on the artifact removal algorithms used to remove
the main sources of interference encountered in the electroencephalogram (EEG) …
the main sources of interference encountered in the electroencephalogram (EEG) …
Reducing noise, artifacts and interference in single-channel emg signals: A review
Electromyography (EMG) is gaining importance in many research and clinical applications,
including muscle fatigue detection, control of robotic mechanisms and prostheses, clinical …
including muscle fatigue detection, control of robotic mechanisms and prostheses, clinical …
A review on empirical mode decomposition in fault diagnosis of rotating machinery
Rotating machinery covers a broad range of mechanical equipment and plays a significant
role in industrial applications. It generally operates under tough working environment and is …
role in industrial applications. It generally operates under tough working environment and is …
Recurrent neural network model with Bayesian training and mutual information for response prediction of large buildings
CA Perez-Ramirez, JP Amezquita-Sanchez… - Engineering …, 2019 - Elsevier
An accurate response prediction model is of great importance in various applications such
as damage detection, structural health monitoring, and vibration control. Development of …
as damage detection, structural health monitoring, and vibration control. Development of …
Variational mode decomposition denoising combined the detrended fluctuation analysis
Y Liu, G Yang, M Li, H Yin - Signal Processing, 2016 - Elsevier
A novel signal denoising method that combines variational mode decomposition (VMD) and
detrended fluctuation analysis (DFA), named DFA–VMD, is proposed in this paper. VMD is a …
detrended fluctuation analysis (DFA), named DFA–VMD, is proposed in this paper. VMD is a …
Computational diagnostic techniques for electrocardiogram signal analysis
Cardiovascular diseases (CVDs), including asymptomatic myocardial ischemia, angina,
myocardial infarction, and ischemic heart failure, are the leading cause of death globally …
myocardial infarction, and ischemic heart failure, are the leading cause of death globally …
Denoising of ECG signals based on noise reduction algorithms in EMD and wavelet domains
This paper presents a new ECG denoising approach based on noise reduction algorithms in
empirical mode decomposition (EMD) and discrete wavelet transform (DWT) domains …
empirical mode decomposition (EMD) and discrete wavelet transform (DWT) domains …
Wheel-bearing fault diagnosis of trains using empirical wavelet transform
H Cao, F Fan, K Zhou, Z He - Measurement, 2016 - Elsevier
Rolling bearings are used widely as wheel bearing in trains. Fault detection of the wheel-
bearing is of great significance to maintain the safety and comfort of train. Vibration signal …
bearing is of great significance to maintain the safety and comfort of train. Vibration signal …
Discrimination and classification of focal and non-focal EEG signals using entropy-based features in the EMD-DWT domain
AB Das, MIH Bhuiyan - biomedical signal processing and control, 2016 - Elsevier
In this paper, a comprehensive analysis of focal and non-focal electroencephalography is
carried out in the empirical mode decomposition and discrete wavelet transform domains. A …
carried out in the empirical mode decomposition and discrete wavelet transform domains. A …
Filter bank property of multivariate empirical mode decomposition
N Ur Rehman, DP Mandic - IEEE transactions on signal …, 2011 - ieeexplore.ieee.org
The multivariate empirical mode decomposition (MEMD) algorithm has been recently
proposed in order to make empirical mode decomposition (EMD) suitable for processing of …
proposed in order to make empirical mode decomposition (EMD) suitable for processing of …