Multiscale sample entropy in heart rate variability of aortic stenosis patients.

José F. Valencia, Alberto Porta, Montserrat Vallverdú, Francesc Clarià, Rafal Baranowski, Ewa Orłowska-Baranowska, Pere Caminal

Research output: Contribution to journalArticle

Abstract

In the present document the multiscale entropy (MSE) methodology has been applied to analyze the complex behavior of the heart rate variability (HRV), in patients with aortic stenosis (AS). A set of healthy voluntaries have been used as a control group. MSE analysis calculates an entropy rate over different time scales to assess the complexity of time series, evaluating short-term and long-term correlations. Daytime and nighttime have been considered to study variations of the complexity inside the same group of population. A statistical analysis showed that entropy was significantly higher in healthy subjects than in AS subjects in all the scales during daytime, with exception at scale 1. During nighttime, entropy in healthy subjects was significantly higher than in AS subjects only in scales from 1 to 7. Multiscale entropy is helpful to characterize AS patients and distinguish them from healthy subjects.

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ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

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