The effect of automated preprocessing of RR interval tachogram on discrimination capability of Heart Rate Variability parameters

Faezeh Marzbanrad, Herbert Jelinek, Ethan Ng, Mikhail Tamayo, Brett Hambly, Craig McLachlan, Slade Matthews, Marimuthu Palaniswami, Ahsan Khandoker

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Heart Rate Variability (HRV) has been extensively investigated for characterizing the autonomic nervous system (ANS) in controlling heart rate. Since ectopic beats, artefacts and noise of the ECG can affect the estimation of HRV features, pre-processing of the RR tachogram can improve the accuracy of HRV analysis and discriminatory power. This paper investigates the effect of different automated preprocessing methods on discriminatory capability of HRV analysis with an example of comparison between different groups of normal and type II diabetic patients with different Angiotensin-Converting Enzyme (ACE) gene polymorphism. Results show that smaller p-values and therefore higher discriminatory capability are found when preprocessing is used, while none of the features can show significant difference if they are estimated from the raw R-R sequence. Secondly, the preprocessing methods do not have the same effect for all HRV features.

Original languageBritish English
Title of host publicationComputing in Cardiology 2013, CinC 2013
Pages483-486
Number of pages4
StatePublished - 2013
Event2013 40th Computing in Cardiology Conference, CinC 2013 - Zaragoza, Spain
Duration: 22 Sep 201325 Sep 2013

Publication series

NameComputing in Cardiology
Volume40
ISSN (Print)2325-8861
ISSN (Electronic)2325-887X

Conference

Conference2013 40th Computing in Cardiology Conference, CinC 2013
Country/TerritorySpain
CityZaragoza
Period22/09/1325/09/13

Fingerprint

Dive into the research topics of 'The effect of automated preprocessing of RR interval tachogram on discrimination capability of Heart Rate Variability parameters'. Together they form a unique fingerprint.

Cite this