A quick heart trace taken during a warm-up trot could identify racehorses at risk of cardiac arrhythmias during ...
This project implements an end-to-end deep learning pipeline for automated heartbeat classification using the MIT-BIH Arrhythmia Dataset. The system performs ECG signal preprocessing, heartbeat ...
This study aims to establish an interpretable disease classification model via machine learning and identify key features related to the disease to assist clinical disease diagnosis based on a ...
Abstract: A Non-stationary signal called an electrocardiogram (ECG) is utilized to evaluate the rate of cardiac beats. Doctors can identify Abstract - Heart Rate Variations (HRV) is one of the major ...
Introduction: Acute coronary syndrome (ACS) is a life-threatening emergency, with occlusion myocardial infarction (OMI) requiring rapid diagnosis and treatment. The 12-lead ECG remains the primary ...
Background: Brain natriuretic peptide (BNP) is a key heart failure biomarker. Single-lead electrocardiograms (ECGs) from wearable devices offer valuable diagnostic and prognostic insights. We ...
ECG signals are vital for diagnosing cardiovascular diseases, but artifacts like power line interference, baseline wander, and motion artifacts hinder accurate interpretation. This study aims to ...
An electrocardiogram or EKG is a testing equipment used to measure the electrical activity of the heart. Using only an Arduino Shield and a set of electrodes, one can create his own EKG, generate a ...