Implementation of deceleration capacity measurement algorithm in MatLab
Journal Title: Applied Medical Informatics - Year 2019, Vol 41, Issue 0
Abstract
Background: Impaired autonomic nervous system (ANS) tonus is involved into the pathogenesisof numerous cardiac diseases, such as atrial fibrillation and malignant ventricular arrhythmias.While numerous electrocardiographic (ECG) markers have been developed in an attempt ofANS tonus estimation, deceleration capacity (DC) proved to be an accurate marker of the vagalactivity. Methods: 24-hours ambulatory ECG recordings of 110 patients were used in DCimplementation. Automatic QRS detection and event classification was performed usingPhysioNet Cardiovascular Signal Toolbox. Afterward, ectopic beats and non-sinus rhythmswere manually excluded from analysis. DC measurement algorithm was implemented usingMatLab version R2018a. Results: Deceleration capacity measurement was implemented usingphase rectified signal averaging method in wavelet scale (s)=2 and timescale (T)=1. Normalconsecutive sinus beats, varying less than 20% in duration compared to previous RR intervalwere included into analysis. On a long-term ECG recording, approximate 40.000 to 100.000 RRintervals are included into analysis. RR anchors are identified as RR intervals longer thanpreceding interval. Equal length segments preceding and succeeding RR anchors are selected.RR tachograms are phase rectified by aligning to each anchor RR interval and averaged. DC iscalculated by formula DC=(X[0]+X[1]-X[-1]-X[-2])/4, where X[0] and X[1] are the averages ofanchor RR and succeeding RR interval, while X[-1] and X[-2] are the averages of the two RRintervals preceding anchor RR interval. Conclusion: DC is one of the most accurate ECG markerof parasympathetic nervous system activity, having the advantage of not being influenced byartifacts, noise, ectopic beats or paroxysmal arrhythmias. DC can be easily implemented inMatLab and used in future clinical studies.
Authors and Affiliations
Paul-Adrian CĂLBUREAN, Marius MĂRUȘTERI
Keywords
Related Articles
- EP ID EP655054
- DOI -
- Views 101
- Downloads 0
Detection of Heart Attack using Cross Wavelet Transformation and Support Vector Machine
Ischemic heart disease is one of the leading causes of death in the world, and includes a wide range of transient forms, including incomplete blood supply to the heart muscle, which cause heart attacks and eventually sud...
Medical learning applications used by undergraduate medical students in Cluj-Napoca: a cross-sectional survey
Introduction: This study explored the utility and attitude towards medical learning applications (MLA) among undergraduate students (general medicine) in Cluj-Napoca and the use of these apps in finding solutions to five...
The Level of Computer Use and the Degree of the Acceptance of Informatics Applied in Medical Research
Young medical graduates are bound to become researchers, as medical science implies constant studying. Documenting, collecting and processing medical data involve a certain degree of computer literacy. The development of...
Structural equation modelling for assessing the psychosocial risk factors of abortion on demand
Introduction: In Romania, an increasing number of women are opting for abortion on demand, despite the large variety of contraceptive methods and their ease of use. Some of the factors that influence the decision of unde...
A comprehensive intelligent compression method on DICOM images
Virtual medical imaging has overgrown in recent years and later implemented in such situations - all of the radiological modalities which include Computed tomography (CT scanners), Magnetic resonance imaging (MRI), ultra...