Purpose Several artificial intelligence (AI) models for the detection and prediction of
cardiovascular-related diseases, including arrhythmias, diabetes, and sleep apnea, have …

In the health care and medical domain, it has been proven challenging to diagnose correctly
many diseases with complicated and interferential symptoms, including arrhythmia …

Accurate detection of pathological conditions in human subjects can be achieved through off-
line analysis of recorded biological signals such as electrocardiograms (ECGs). However …

Technological advances on the development of mobile devices, medical sensors, and
wireless communication systems support a new generation of unobtrusive, portable, and …

Automatic recognition of arrhythmias is particularly important in the diagnosis of heart
diseases. This study presents an electrocardiogram (ECG) recognition system based on …

Wearable electrocardiogram (ECG) devices can provide real-time, long-term, non-invasive
and comfortable ECG monitoring for premature beats (PB) assessment (typically presenting …

In the last decade, cuffless blood pressure measurement technology has been widely
studied because it could be applied to a wearable apparatus. Electrocardiography (ECG) …

In the past decades, the electrocardiogram (ECG) has been investigated as a promising
biometric by exploiting the subtle discrepancy of ECG signals between subjects. However …

Objective. Learning to classify cardiac abnormalities requires large and high-quality labeled
datasets, which is a challenge in medical applications. Small datasets from various sources …

This study involved fabricating barbed microtip-based electrode arrays by using silicon wet
etching. KOH anisotropic wet etching was employed to form a standard pyramidal microtip …