This study presents a 2-stage heartbeat classifier of supraventricular (SVB) and ventricular (VB) beats. Stage 1 makes computationally-efficient classification of SVB-beats, using simple correlation threshold criterion for finding close match with a ...
Computational and mathematical methods in medicine
Sep 13, 2015
The aim of this study was to determine the accuracy of fuzzy rule-based classification that could noninvasively predict CAD based on myocardial perfusion scan test and clinical-epidemiological variables. This was a cross-sectional study in which the ...
BACKGROUND: Heart rate variability (HRV) has been widely used in the non-invasive evaluation of cardiovascular function. Recent studies have also attached great importance to the cardiac diastolic period variability (DPV) examination. Short-term vari...
BACKGROUND AND PURPOSE: Culprit coronary artery assessment in the triage ECG of patients with suspected acute coronary syndrome (ACS) is relevant a priori knowledge preceding percutaneous coronary intervention (PCI). We compared a model-based automat...
Non-invasively reconstructing the cardiac transmembrane potentials (TMPs) from body surface potentials can act as a regression problem. The support vector regression (SVR) method is often used to solve the regression problem, however the computationa...
IEEE transactions on bio-medical engineering
Feb 10, 2015
Automatic processing and accurate diagnosis of pathological electrocardiogram (ECG) signals remains a challenge. As long-term ECG recordings continue to increase in prevalence, driven partly by the ease of remote monitoring technology usage, the need...
Most acquired cardiovascular diseases are more common in older people, and the biological mechanisms and manifestations of aging provide insight into cardiovascular pathophysiology. Measuring aging within the cardiovascular system may help to better ...
Stabilizing the cardiac rhythm is imperative for preserving cardiovascular health and preventing life-threatening arrhythmias. The stabilization of the heartbeat through traditional control methods presents significant challenges due to the intricate...
Zero-dimensional (0D) cardiovascular models are reduced-order models aimed at studying the global dynamics of the whole circulation system or transport within it. They are employed to obtain estimates of important biomarkers for surgery planning and ...
In this work, we developed deep neural networks for the fast and comprehensive estimation of the most salient features of aortic blood flow. These features include velocity magnitude and direction, 3D pressure, and wall shear stress. Starting from 40...
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