Abstract

The novel corona virus disease (COVID-19) is a deadly SARS- COV-2 communicable virus causing the world economy to crash. COVID-19, which causes interstitial pneumonitis and severe acute respiratory distress syndrome (ARDS), primarily affects the lungs multiple organs, especially the cardiovascular system. The ability of this virus to spread through human-to - human and surface-to-human transmission contributes to a devastating process in the world Biological signal analysis based on computer system allows medical officers to manage Covid-19 tasks such as intensive care ECG monitoring, fatal ventricular fibrillation, etc. The most common complications include heart dysfunctions such as tachycardia, bradycardia, ventricular fibrillation, cardiac arrhythmias, heart injury [highly responsive troponin I (hs-cTnI) elevation and creatine kinase, fulminant myocarditis, heart failure, pulmonary embolism, and disseminated intravascular coagulation (DIC). Mechanistically, SARS-CoV-2 binds to transmembrane angiotensin-converting enzyme 2 (ACE2), a homologue of ACE, after proteolytic cleavage of its S protein by a serine protease, to join type 2 pneumocytes, macrophages, perivascular pericytes, and cardiomyocytes. This can result in myocardial dysfunction and injury, endothelial dysfunction, plaque instability, microvascular dysfunction, and myocardial infarction (MI). In this research, for classification purposes, the heart pulse base signal and characteristics such as spectral entropy, largest lyapunov exponent, Poincare plot and detrended fluctuation analysis are extracted and presented. The Poincare plot RR intervals summarise the RR time series obtained in one image from an ECG, and the quantity of a time interval derives the HRV information length. The prediction of heart rate fluctuation due to Covid or other heart problems is made simpler by this study.The better accuracy level in diagnosing heart pulse irregularity using Artificial Neural network(ANN) is an integer value (0 to 4).The processing time for analyzing heart dysfunctionalties is 0.05 s using ANN.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call