ArticleJournal of healthcare engineering2018
Improved Multiscale Entropy Technique with Nearest-Neighbor Moving-Average Kernel for Nonlinear and Nonstationary Short-Time Biomedical Signal Analysis.
Article in Journal of healthcare engineering, 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.
- Gait analysis for Parkinson's disease using multiscale entropy.Neurodegenerative disease management · 2025Review
- Complexity AF score as a novel marker of atrial fibrillation instability.Scientific reports · 2024Article
- The role of the Cx43/Cx45 gap junction voltage gating on wave propagation and arrhythmogenic activity in cardiac tissue.Scientific reports · 2023Article
- A novel approach for quantitative electrogram analysis for driver identification: Implications for ablation in persistent atrial fibrillation.Frontiers in cardiovascular medicine · 2022Article
- Novel mapping techniques for rotor core detection using simulated intracardiac electrograms.Journal of cardiovascular electrophysiology · 2021Article
- Similarity Score for the Identification of Active Sites in Patients With Atrial Fibrillation.Frontiers in physiology · 2021Article
- [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
- Towards the Development of Nonlinear Approaches to Discriminate AF from NSR Using a Single-Lead ECG.Entropy (Basel, Switzerland) · 2020Article
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5 authors.
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Abstract
Analysis of biomedical signals can yield invaluable information for prognosis, diagnosis, therapy evaluation, risk assessment, and disease prevention which is often recorded as short time series data that challenges existing complexity classification algorithms such as Shannon entropy (SE) and other techniques. The purpose of this study was to improve previously developed multiscale entropy (MSE) technique by incorporating nearest-neighbor moving-average kernel, which can be used for analysis of nonlinear and non-stationary short time series physiological data. The approach was tested for robustness with respect to noise analysis using simulated sinusoidal and ECG waveforms. Feasibility of MSE to discriminate between normal sinus rhythm (NSR) and atrial fibrillation (AF) was tested on a single-lead ECG. In addition, the MSE algorithm was applied to identify pivot points of rotors that were induced in
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