This paper presents an extensive review on the artifact removal algorithms used to remove
the main sources of interference encountered in the electroencephalogram (EEG) …

Electromyography (EMG) is gaining importance in many research and clinical applications,
including muscle fatigue detection, control of robotic mechanisms and prostheses, clinical …

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 …

An accurate response prediction model is of great importance in various applications such
as damage detection, structural health monitoring, and vibration control. Development of …

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 …

This paper presents a new ECG denoising approach based on noise reduction algorithms in
empirical mode decomposition (EMD) and discrete wavelet transform (DWT) domains …

Cardiovascular diseases (CVDs), including asymptomatic myocardial ischemia, angina,
myocardial infarction, and ischemic heart failure, are the leading cause of death globally …

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 …

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 …

The multivariate empirical mode decomposition (MEMD) algorithm has been recently
proposed in order to make empirical mode decomposition (EMD) suitable for processing of …