In this paper, a novel algorithm based on a convolutional neural network (CNN) is proposed
for myocardial infarction detection via multilead electrocardiogram (ECG). A beat …

This paper proposes a method that predicts the onset of paroxysmal atrial fibrillation (PAF),
using heart rate variability (HRV) segments that are shorter than those applied in existing …

This study presents two types of data hiding methods based on coefficient alignment for
electrocardiogram (ECG) signals, namely, lossy and reversible ECG steganographys. The …

The design of analog and mixed-signal integrated circuits (ICs) is intricate due to the
continuous nature of the signals handled. Still, it is also strongly affected by the physical …

In this paper, the concept of multi-objective optimization is introduced in the automation of
the placement task in analog integrated circuits layout design. To bridge the difficulties found …

Hiding data in electrocardiogram signals are a big challenge due to the embedded
information that can hamper the accuracy of disease detection. On the other hand, hiding …

The developing prominence of edge computing and Internet of Things-based wearables
coupled with body sensors offer us a unique idea of integrating the Diagnosis …

This work is the answer to the so far unsolved problem of generation of integrated circuits
topography for current mode circuits. Synthesis methods corresponding to already existing …

Methods, devices, and systems for monitoring heart rate variability (HRV). The HRV
monitoring systems and devices are adapted to give immediate feedback to the Subject …

Cardiovascular disease (CVD) patients need continuous monitoring of bio-signals and
regular hospital visit to improve health conditions. A portable health monitoring device can …