Entropy characteristics of heart rate wavelet multiscale components in epileptic children before and after seizures

Riccardo Pernice, Luca Faes, Anton Popov, Volodymyr Kharytonov, Ivan Kotiuchyi, Ivan Kotiuchyi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this work, we analyze the information content of the multiple time scale components of heart rate variability (HRV) in children with focal epilepsy. HRV components are extracted from 30 pediatric patients, monitored 10 min and 10 s before and after focal epileptic seizures, using wavelet multiscale decomposition (with 5, 15, 30, 60, 120, 180 s time scale), and then characterized computing Entropy (E), permutation entropy (PE), conditional entropy (CE) and information storage (IS). Moving from preictal to postictal windows, we find statistically significant differences in the CE and IS values of HRV components at short time scales, which reflect autonomic imbalance and appear as potential candidates of descriptive features for HRV monitoring in epilepsy.
Original languageEnglish
Title of host publication2020 11th Conference of the European Study Group on Cardiovascular Oscillations (ESGCO)
Pages1-2
Number of pages2
Publication statusPublished - 2020

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Modelling and Simulation
  • Cardiology and Cardiovascular Medicine
  • Health Informatics
  • Physiology (medical)
  • Instrumentation

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