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November 1, 2009IEEE Engineering in Medicine and Biology Magazine

Approximate entropy for all signals

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Population

Synthetic and experimental data (signals)

Comparison

New method based on a heuristic stochastic model… vs Standard calculation of all choices of r values

Design

Other

Authors

KCKi H. ChonCSChristopher G. ScullySLSheng Lu

Discussion

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Overview

Enables efficient ApEn computation for biomedical signals; leaves open prospective validation before clinical use.

Structured PICO

P
Population
Synthetic and experimental data (signals)
I
Intervention
New method based on a heuristic stochastic model for automatic selection of maximum approximate entropy (ApEn)
C
Comparator
Standard calculation of all choices of r values
O
Outcome
Accuracy of estimating maximum ApEn

A new heuristic stochastic model allows for the automatic and computationally efficient selection of the maximum approximate entropy value for signal analysis.

Cite This Study

Chon et al. (2009) studied this question.

synapsesocial.com/papers/6a89cb58af65c378f7fd49f0https://doi.org/10.1109/memb.2009.934629
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  5. 5Multiscale Entropy Analysis of Complex Physiologic Time Series2002 · 3,232 citations