Heart failure prognostic algorithm using Spectral Analysis and MATLAB software

Fourier analysis for biological signals is based on the use of the infinite sum of sines and cosines that allows modeling: the periodic functioning of the heart, its amplitude, frequency, and phase period, transforming these signals into images called ECG, based on studies and programs that model th...

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Bibliographic Details
Published in:Bionatura Journal Vol. 1; no. 1; pp. 1 - 27
Main Authors: Segundo Fabián, Siza Moposita, Miguel Ángel, Sáez Paguay, Yesenia Maricela, Fiallos Godoy, Siza Gualpa, Ricardo Fabián
Format: Journal Article
Language:English
Spanish
Published: Quito Editorial Clinical Biotec 15.03.2024
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ISSN:3020-7886, 3020-7886
Online Access:Get full text
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Summary:Fourier analysis for biological signals is based on the use of the infinite sum of sines and cosines that allows modeling: the periodic functioning of the heart, its amplitude, frequency, and phase period, transforming these signals into images called ECG, based on studies and programs that model the ideal functioning of the heart. In this work, a mathematical algorithm has been designed to predict the cardiac pathology called bradycardia, which relates the prolongation of the monthly QT interval in the order of 10-4 seconds/month in a time of 10 years with the ventricular alteration. MATLAB software and spectral analysis are used to contrast the spectrum without pathology, which contains harmonics of greater amplitude, with a spectrum already with pathology that reaches heart failure, where the most significant number of harmonics are grouped in the first values, and then the model with an exponential function the delay of the QT interval in the ECG, concluding that up to 40 months after the onset of the pathology, the patient can counteract the disease. In comparison, by 80 months, difficulties arise, even the disease becomes irreversible in the last months, and the blood-propelling organ ceases to function. Keywords: Heart Failure Prognostic, Bradycardia, Fourier Series, Spectral Analysis.
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ISSN:3020-7886
3020-7886
DOI:10.21931/BJ/2024.01.01.12