DocumentCode
674498
Title
The effect of automated preprocessing of RR interval tachogram on discrimination capability of Heart Rate Variability parameters
Author
Marzbanrad, Faezeh ; Jelinek, Herbert ; Ng, Ethan ; Tamayo, Mikhail ; Hambly, Brett ; McLachlan, Craig ; Matthews, Slade ; Palaniswami, Marimuthu ; Khandoker, Ahsan
Author_Institution
Univ. of Melbourne, Parkville, VIC, Australia
fYear
2013
fDate
22-25 Sept. 2013
Firstpage
483
Lastpage
486
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.
Keywords
biochemistry; bioelectric potentials; diseases; electrocardiography; enzymes; feature extraction; genetics; medical signal processing; molecular biophysics; statistical analysis; ACE gene polymorphism; ECG artefacts; ECG noise; HRV analysis; HRV feature estimation; R-R sequence estimation; RR interval tachogram; angiotensin-converting enzyme; automated preprocessing methods; autonomic nervous system characterization; ectopic beats; electrocardiography; heart rate variability parameters; type II diabetic patients; Abstracts; Heart rate variability; Myocardium; Statistical analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Computing in Cardiology Conference (CinC), 2013
Conference_Location
Zaragoza
ISSN
2325-8861
Print_ISBN
978-1-4799-0884-4
Type
conf
Filename
6713419
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