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 PaperResearchpeer-review

4 Citations (Scopus)


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 languageEnglish
Title of host publicationComputing in Cardiology 2013
Subtitle of host publicationSeptember 22-25, 2013, Zaragoza, Spain [proceedings]
EditorsAlan Murray
Place of PublicationVancouver, Canada
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages4
ISBN (Electronic)9781479908868
ISBN (Print)9781479908844
Publication statusPublished - 2013
Externally publishedYes
EventComputing in Cardiology Conference 2013 - Zaragoza, Spain
Duration: 22 Sep 201325 Sep 2013


ConferenceComputing in Cardiology Conference 2013
Abbreviated titleCINC 2013

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