Methodological comparisons of heart rate variability analysis in patients with type 2 diabetes and angiotensin converting enzyme polymorphism

Faezeh Marzbanrad, Ahsan H. Khandoker, Brett D. Hambly, Ethan Ng, Michael Tamayo, Yaxin Lu, Slade Matthews, Chandan Karmakar, Marimuthu Palaniswami, Herbet F. Jelinek, McLachlan Craig

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8 Citations (Scopus)


Angiotensin converting enzyme (ACE) polymorphism has been shown to be important in hypertension progression and also in diabetes complications, especially associated with heart disease. Heart rate variability (HRV) is an established measure for classification of autonomic function regulating heart rate, based on the interbeat interval time series derived from a raw ECG recording. Results of this paper show that the length (number of interbeat intervals) and preprocessing of the tachogram affect the HRV analysis outcome. The comparison was based on tachogram lengths of 250, 300, 350, and 400 RR-intervals and five preprocessing approaches. An automated adaptive preprocessing method for the heart rate biosignal and tachogram length of 400 interbeat intervals provided the best classification. HRV results differed for the Type 2 Diabetes Mellitus (T2DM) group between the I/I genotype and the I/D and D/D genotypes, whereas for controls there was no significant difference in HRV between genotypes. Selecting an appropriate length of recording and automated preprocessing has confirmed that there is an effect of ACE polymorphism including the I/I genotype and that I/I should not be combined with I/D genotype in determining the extent of autonomic modulation of the heart rate.
Original languageEnglish
Pages (from-to)55-63
Number of pages9
JournalIEEE Journal of Biomedical and Health Informatics
Issue number1
Publication statusPublished - Jan 2016
Externally publishedYes


  • Angiotensin converting enzyme (ACE) polymorphism
  • Genotypes
  • Heart rate variability analysis
  • Preprocessing
  • Tachogram length
  • Type-2 diabetes

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