Paper Info
Title
Influence of QRS complex detection errors on entropy algorithms. Application to heart rate variability discrimination.
Abstract
Signal entropy measures such as approximate entropy (ApEn) and sample entropy (SampEn) are widely used in heart rate variability (HRV) analysis and biomedical research. In this article, we analyze the influence of QRS detection errors on HRV results based on signal entropy measures. Specifically, we study the influence that QRS detection errors have on the discrimination power of ApEn and SampEn using the cardiac arrhythmia suppression trial (CAST) database. The experiments assessed the discrimination capability of ApEn and SampEn under different levels of QRS detection errors. The results demonstrate that these measures are sensitive to the presence of ectopic peaks: from a successful classification rate of 100%, down to a 75% when spikes are present. The discriminating capability of the metrics degraded as the number of misdetections increased. For an error rate of 2% the segmentation failed in a 12.5% of the experiments, whereas for a 5% rate, it failed in a 25%.
Year
DOI
Venue
2013
10.1016/j.cmpb.2012.10.014
Computer Methods and Programs in Biomedicine
Keywords
Field
DocType
successful classification rate,signal entropy measure,qrs detection error,qrs complex detection error,error rate,discrimination power,sample entropy,hrv result,approximate entropy,entropy algorithm,heart rate variability discrimination,discrimination capability,entropy measure,heart rate variability
Approximate entropy,Sample entropy,Pattern recognition,Segmentation,Heart rate variability,Word error rate,Cardiac Arrhythmia Suppression Trial,QRS complex,Artificial intelligence,Statistics,Classification rate,Mathematics
Journal
Volume
Issue
ISSN
110
1
1872-7565
Citations 
PageRank 
References 
6
0.53
10
Authors
5
Name
Order
Citations
PageRank
Antonio Molina-Picó1386.70
D. Cuesta-Frau214923.78
Pau Miró-Martínez3346.21
Sandra Oltra-Crespo4305.02
Mateo Aboy529740.03