Open AccessNARX NEUROMORPHIC SOFTWARE FOR ECG WAVE PREDICTION
Author(s) -
T. Dima,
Svetlana Pitina
Publication year - 2021
Publication title -
9th international conference "distributed computing and grid technologies in science and education"
Language(s) - English
Resource type - Conference proceedings
DOI - 10.54546/mlit.2021.30.97.001
Subject(s) - nonlinear autoregressive exogenous model , qrs complex , software , neuromorphic engineering , computer science , autoregressive model , artificial intelligence , artificial neural network , medicine , mathematics , statistics , programming language
ECG wave prediction with non-linear autoregressive exogenous neuromorphic (NARX) software is anovel method aimed at Holter monitoring and early warning. Such predictions are important incomparing the underlying QRS complex of the ECG-wave with the slowly deteriorating waves (orarrythmia) in cardiac patients. A deep Q-wave for instance (such as 1/4 of the R-wave) is a typicalsign of (inferior wall) myocardial necrosis - associated in most cases with vascular dysfunction. It isimportant to have a rolling predictor - slow ECG wave degradation being normal. A real-timepredictor takes into account a suite of influencing parameters (body temperature, effort, currentmedication, sugar levels, stress, etc), being much better suited in making a call for "normal" vs."anomalous" ECG waves, rather than some outdated reference waves. Although this research is in itsbegining, it shows encouraging results, which clinical studies can conclude as to how effectivethe approach may be.