Timely detection of cardiac abnormalities from an Electrocardiogram (ECG) signal is very
essential. This requires its appropriate and efficient processing. In the literature, most of the …

The health of the brain and muscles depends on the proper analysis of
electroencephalogram and electromyogram signals without noise. The latter blends into the …

Electrocardiogram (ECG) plays an important role in diagnostics of cardiac diseases. In
general, ECG signals are affected by noises during data acquisition. For accurate treatment …

Complex oil and gas two-phase flow exists within an aero-engines bearing cavity scavenge
pipe, prone to lubricated self-ignition and coking. Lubricant system designers must be able …

The empirical wavelet transforms and Capon time-frequency applications are used in this
work. EMG and EEG are non-invasive ways to measure muscle activity and the electrical …

This paper discusses in detail the extraction methods of the foetal Electrocardiogram (fECG)
signal from the non-invasive maternal Electrocardiogram (mECG) and enhancement …

Electromyography (EMG) is a diagnostic tool commonly used to assess the electrical activity
of muscles. This test can help diagnose various neuromuscular conditions, evaluate muscle …

Selection and implementation of optimal order digital filter for denoising ECG signal on
FPGA, based on Signal to Noise Ratio (SNR), error and accuracy using wavelet toolbox is a …

This work treats the filtering of artifacts that interfered with the ECG signals by the different
denoising methods for ameliorate the reliability accuracy. During ECG measurement, there …

The electroencephalogram (EEG) is a test that determines brain activity. The existence of
artifacts in EEG can naturally decrease the smoothness of the analysis of the biomedical …