ArticleEntropy (Basel, Switzerland)2018
Coarse-Graining Approaches in Univariate Multiscale Sample and Dispersion Entropy.
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 17 papers.
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17 citing papers in PubMed, 66 citations in OpenAlex.
- An ECG feature extraction method based on GASF and MPRE2D for the detection of congestive heart failure.Physical and engineering sciences in medicine · 2026Article
- Multiscale dispersion entropy of resting-state EEG in older adults with Alzheimer's disease, mild cognitive impairment, and remitted major depressive disorder.Journal of Alzheimer's disease : JAD · 2026Article
- Fault diagnosis of aero-engines using transfer dispersion entropy and dispersion patterns.PloS one · 2026Article
- Benefits of Zero-Phase or Linear Phase Filters to Design Multiscale Entropy: Theory and Application.Entropy (Basel, Switzerland) · 2024Article
- Multiscale Entropy-Based Feature Extraction for the Detection of Instability Inception in Axial Compressors.Entropy (Basel, Switzerland) · 2024Article
- EEG Entropy in REM Sleep as a Physiologic Biomarker in Early Clinical Stages of Alzheimer's Disease.Journal of Alzheimer's disease : JAD · 2023Article
- Detection of Oculomotor Dysmetria From Mobile Phone Video of the Horizontal Saccades Task Using Signal Processing and Machine Learning Approaches.IEEE access : practical innovations, open solutions · 2022Article
- A Bearing Fault Diagnosis Method Based on PAVME and MEDE.Entropy (Basel, Switzerland) · 2021Article
- Coordinated Approach Fusing RCMDE and Sparrow Search Algorithm-Based SVM for Fault Diagnosis of Rolling Bearings.Sensors (Basel, Switzerland) · 2021Article
- Article
- [Research progress on multiscale entropy algorithm and its application in neural signal analysis].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2020Article
- Standard multiscale entropy reflects neural dynamics at mismatched temporal scales: What's signal irregularity got to do with it?PLoS computational biology · 2020Article
- A Novel Microwave Treatment for Sleep Disorders and Classification of Sleep Stages Using Multi-Scale Entropy.Entropy (Basel, Switzerland) · 2020Article
- EEG Characterization of the Alzheimer's Disease Continuum by Means of Multiscale Entropies.Entropy (Basel, Switzerland) · 2019Article
- Partial Discharge Fault Diagnosis Based on Multi-Scale Dispersion Entropy and a Hypersphere Multiclass Support Vector Machine.Entropy (Basel, Switzerland) · 2019Article
- Noise Reduction Method of Underwater Acoustic Signals Based on CEEMDAN, Effort-To-Compress Complexity, Refined Composite Multiscale Dispersion Entropy and Wavelet Threshold Denoising.Entropy (Basel, Switzerland) · 2018Article
- Evaluation of Systems' Irregularity and Complexity: Sample Entropy, Its Derivatives, and Their Applications across Scales and Disciplines.Entropy (Basel, Switzerland) · 2018Article
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2 authors at 1 institution in 1 country.
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Abstract
The evaluation of complexity in univariate signals has attracted considerable attention in recent years. This is often done using the framework of Multiscale Entropy, which entails two basic steps: coarse-graining to consider multiple temporal scales, and evaluation of irregularity for each of those scales with entropy estimators. Recent developments in the field have proposed modifications to this approach to facilitate the analysis of short-time series. However, the role of the downsampling in the classical coarse-graining process and its relationships with alternative filtering techniques has not been systematically explored yet. Here, we assess the impact of coarse-graining in multiscale entropy estimations based on both Sample Entropy and Dispersion Entropy. We compare the classical moving average approach with low-pass Butterworth filtering, both with and without downsampling, and empirical mode decomposition in Intrinsic Multiscale Entropy, in selected synthetic data and two real physiological datasets. The results show that when the sampling frequency is low or high, downsampling respectively decreases or increases the entropy values. Our results suggest that, when dealing with long signals and relatively low levels of noise, the refine composite method makes little difference in the quality of the entropy estimation at the expense of considerable additional computational cost. It is also found that downsampling within the coarse-graining procedure may not be required to quantify the complexity of signals, especially for short ones. Overall, we expect these results to contribute to the ongoing discussion about the development of stable, fast and robust-to-noise multiscale entropy techniques suited for either short or long recordings.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.