In recent years, cardiovascular diseases are on the rise, and they entail enormous health
burdens on global economies. Cardiac vibrations yield a wide and rich spectrum of essential …

Cardiovascular diseases affect approximately 50 million people worldwide; thus, heart
disease prevention is one of the most important tasks of any health care system. Despite the …

Electrocardiogram (ECG) signal is nonlinear and non-stationary weak signal which reflects
whether the heart is functioning normally or abnormally. ECG signal is susceptible to various …

Abstract The Ensemble Empirical Mode Decomposition (EEMD) is a noise assisted method
that may sometimes provide a significant improvement on Empirical Mode Decomposition …

Accurate classification of electrocardiogram (ECG) signals is of significant importance for
automatic diagnosis of heart diseases. In order to enable intelligent classification of …

Understanding the impact forces exerted by debris flows is limited by a lack of direct field
measurements and validated numerical models. In this study, we use real‐time impact‐force …

A novel noise filtering algorithm based on ensemble empirical mode decomposition (EEMD)
is proposed to remove artifacts in electrocardiogram (ECG) traces. Three noise patterns with …

Today, remote machine condition monitoring is popular due to the continuous advancement
in wireless communication. Bearing is the most frequently and easily failed component in …

Classifying electrocardiogram (ECG) heartbeats for arrhythmic risk prediction is a
challenging task due to minute variations in the amplitude, duration and morphology of the …

In recent years, Electrocardiogram (ECG) plays an imperative role in heart disease
diagnostics, Human Computer Interface (HCI), stress and emotional states assessment, etc …