ArticleEntropy (Basel, Switzerland)2018
Combination of R-R Interval and Crest Time in Assessing Complexity Using Multiscale Cross-Approximate Entropy in Normal and Diabetic Subjects.
Article in Entropy (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Novel Application of Multiscale Cross-Approximate Entropy for Assessing Early Changes in the Complexity between Systolic Blood Pressure and ECG R-R Intervals in Diabetic Rats.Entropy (Basel, Switzerland) · 2022Article
- Variational Embedding Multiscale Sample Entropy: A Tool for Complexity Analysis of Multichannel Systems.Entropy (Basel, Switzerland) · 2021Article
- Discrimination of Patients with Varying Degrees of Coronary Artery Stenosis by ECG and PCG Signals Based on Entropy.Entropy (Basel, Switzerland) · 2021Article
- Optical coherence tomography angiography measures blood pulsatile waveforms at variable tissue depths.Quantitative imaging in medicine and surgery · 2021Article
- A Novel Hybrid Approach for Partial Discharge Signal Detection Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Approximate Entropy.Entropy (Basel, Switzerland) · 2020Article
- A Smart Service Platform for Cost Efficient Cardiac Health Monitoring.International journal of environmental research and public health · 2020Review
- (Multiscale) Cross-Entropy Methods: A Review.Entropy (Basel, Switzerland) · 2019Review
- Entropy Measures in Analysis of Head up Tilt Test Outcome for Diagnosing Vasovagal Syncope.Entropy (Basel, Switzerland) · 2018Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
The present study aimed at testing the hypothesis that application of multiscale cross-approximate entropy (MCAE) analysis in the study of nonlinear coupling behavior of two synchronized time series of different natures [i.e., R-R interval (RRI) and crest time (CT, the time interval from foot to peakof a pulse wave)] could yield information on complexity related to diabetes-associated vascular changes. Signals of a single waveform parameter (i.e., CT) from photoplethysmography and RRI from electrocardiogram were simultaneously acquired within a period of one thousand cardiac cycles for the computation of different multiscale entropy indices from healthy young adults (n = 22) (Group 1), upper-middle aged non-diabetic subjects (n = 34) (Group 2) and diabetic patients (n = 34) (Group 3). The demographic (i.e., age), anthropometric (i.e., body height, body weight, waist circumference, body-mass index), hemodynamic (i.e., systolic and diastolic blood pressures), and serum biochemical (i.e., high- and low-density lipoprotein cholesterol, total cholesterol, and triglyceride) parameters were compared with different multiscale entropy indices including small- and large-scale multiscale entropy indices for CT and RRI [MEI
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