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Sample Entropy in Electrocardiogram During Atrial Fibrillation.

Takuya Horie1, Naoto Burioka2, Takashi Amisaki3

  • 1Division of Clinical Laboratory, Tottori University Hospital, Yonago 683-8504, Japan.

Yonago Acta Medica
|March 31, 2018
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Summary

Sample entropy (SampEn) analysis of electrocardiogram (ECG) signals reveals higher complexity in patients with atrial fibrillation (AF). This nonlinear analysis may serve as a new index for evaluating complex cardiac systems in AF patients.

Keywords:
atrial fibrillationelectrocardiogramsample entropytime-series data

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Area of Science:

  • Cardiology
  • Biomedical Engineering
  • Nonlinear Dynamics

Background:

  • Atrial fibrillation (AF) is a common arrhythmia with a high risk of thromboembolism.
  • Nonlinear analyses, including sample entropy (SampEn), are used to quantify biological signal complexity.
  • Previous studies have utilized SampEn to analyze various biological signals.

Purpose of the Study:

  • To examine and compare SampEn values in ECG signals from patients with and without chronic AF.
  • To assess the potential of SampEn as a measure of complexity in cardiac time-series data.

Main Methods:

  • ECG signals were recorded from 34 subjects without arrhythmia and 15 patients with chronic AF.
  • Time-series data were derived from ECG signals, and SampEn was calculated.
  • Time-delayed three-dimensional space plots were constructed using time lags of τ = 1 and τ = 5.

Main Results:

  • SampEn values were significantly higher in the chronic AF group (0.392 ± 0.158 for τ = 1, 0.759 ± 0.246 for τ = 5) compared to the non-arrhythmia group (0.252 ± 0.114 for τ = 1, 0.533 ± 0.163 for τ = 5).
  • Statistical significance was observed for both time lags (P < 0.01 for τ = 1, P < 0.004 for τ = 5).
  • Time-delayed three-dimensional space plots showed better loop definition for τ = 5.

Conclusions:

  • ECG signals from chronic AF patients exhibit higher SampEn values, indicating increased time-series complexity.
  • SampEn demonstrates potential as a novel index for evaluating the complexity of cardiac systems in AF.
  • This nonlinear measure may aid in understanding the dynamics of AF.