Sparse signals are characterized by a few nonzero coefficients in one of their transformation
domains. This was the main premise in designing signal compression algorithms …

Cardiovascular disease (CVD) is one of the most widespread health problems with
unpredictable and life-threatening consequences. The electrocardiogram (ECG) is …

In social settings, individuals interact through webs of relationships. Each individual is a
node in a complex network (or graph) of interdependencies and generates data, lots of data …

We propose a practical system design for biometrics authentication based on
electrocardiogram (ECG) signals collected from mobile or wearable devices. The ECG …

Compressive sensing has emerged as an area that opens new perspectives in signal
acquisition and processing. It appears as an alternative to the traditional sampling theory …

Objective: The electrocardiogram (ECG) follows a characteristic shape, which has led to the
development of several mathematical models for extracting clinically important information …

To diagnose health status of the heart, heart monitoring systems use heart signals produced
during each cardiac cycle. Many types of signals are acquired to analyze heart functionality …

Abstract Objective: Globally, cardiovascular diseases (CVDs) are one of the most leading
causes of death. In medical screening and diagnostic procedures of CVDs …

Intelligent tires can be used for a wide array of applications ranging from tire pressure
monitoring to analyzing tire/road interactions, wheel loading, and tread wear monitoring. In …

In spite of development in digital storage and communication technology, the demand for
data compression is ever increasing. The ECG data requires about 40–50 MB per channel …