6533b862fe1ef96bd12c62e6
RESEARCH PRODUCT
Entropy characteristics of heart rate wavelet multiscale components in epileptic children before and after seizures
Ivan KotiuchyiAnton PopovVolodymyr KharytonovRiccardo PerniceLuca Faessubject
Conditional entropyconditional entropy (CE)business.industryPattern recognitionHeart Rate Variability (HRV)medicine.diseaseinformation storage (IS)EpilepsyWaveletHeart rateSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaMultiple timemedicineEntropy (information theory)Heart rate variabilityArtificial intelligenceTime seriesbusinessentropywavelet transformMathematicsdescription
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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2020-07-01 |