Discrimination power of long-term heart rate variability measures for Chronic Heart Failure detection

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Melillo, Paolo, Fusco, Roberta, Sansone, Mario, Bracale, Marcello and Pecchia, Leandro (2011) Discrimination power of long-term heart rate variability measures for Chronic Heart Failure detection. Medical and Biological Engineering and Computing, 49 (1). pp. 67-74. ISSN 0140-0118

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Abstract

The aim of this study was to investigate the discrimination power of standard long-term Heart Rate Variability (HRV) measures for the diagnosis of Chronic Heart Failure (CHF).

We performed a retrospective analysis on 4 public Holter databases, analyzing the data of 72 normal subjects and 44 patients suffering from CHF. To assess the discrimination power of HRV measures, we adopted an exhaustive search of all possible combinations of HRV measures and we developed classifiers based on Classification and Regression Tree (CART) method, which is a non-parametric statistical technique.

We found that the best combination of features is: Total spectral power of all NN intervals up to 0.4 Hz (TOTPWR), square Root of the Mean of the Sum of the Squares of Differences between adjacent NN intervals (RMSSD) and Standard Deviation of the Averages of NN intervals in all 5-minute segments of a 24-hour recording (SDANN). The classifiers based on this combination achieved a specificity rate and a sensitivity rate of 100.00% and 89.74% respectively.

Our results are comparable with other similar studies, but the method we used is particularly valuable because it provides an easy to understand description of classification procedures, in terms of intelligible “if … then …” rules. Finally, the rules obtained by CART are consistent with previous clinical studies.

Item Type: Article
RIS ID: https://nottingham-repository.worktribe.com/output/1010333
Additional Information: The original publication is available at www.springerlink.com
Keywords: Heart Rate Variability (HRV), Chronic Heart Failure (CHF), worsening assessment, Classification and regression tree (CART)
Schools/Departments: University of Nottingham, UK > Faculty of Engineering
Identification Number: 10.1007/s11517-010-0728-5
Related URLs:
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URL Type
http://www.springerlink.com/
Publisher
Depositing User: Pecchia, Dr Leandro
Date Deposited: 13 Feb 2012 10:01
Last Modified: 04 May 2020 20:23
URI: https://eprints.nottingham.ac.uk/id/eprint/1579

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