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Multiscale entropy analysis of biological signals
Physical Review E, 2005Traditional approaches to measuring the complexity of biological signals fail to account for the multiple time scales inherent in such time series. These algorithms have yielded contradictory findings when applied to real-world datasets obtained in health and disease states.
Madalena, Costa +2 more
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Time-Shift Multiscale Entropy Analysis of Physiological Signals [PDF]
Entropy, 2017 Measures of predictability in physiological signals using entropy measures have been widely applied in many areas of research. Multiscale entropy expresses different levels of either approximate entropy or sample entropy by means of multiple factors for generating multiple time series, enabling the capture of more useful information than using a scalar
Tuan D Pham, Pham Tuan D
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Multivariate multiscale entropy of financial markets
Communications in Nonlinear Science and Numerical Simulation, 2017zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yunfan Lu, Jun Wang
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Analysis of Impact Factors of Multiscale Entropy
2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2018Multiscale entropy (MSE) is an algorithm to quantify the complexity of physiological dynamics system. It has been widely applied in different fields to probe into inherent information of biological signals. Although it is important for us to understand how these differences of signals patterns affect the trend of MSE, the factors impacting MSE and ...
Teng Zhang +4 more
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Multiscale entropy analysis of human gait dynamics
Physica A: Statistical Mechanics and its Applications, 2003We compare the complexity of human gait time series from healthy subjects under different conditions. Using the recently developed multiscale entropy algorithm, which provides a way to measure complexity over a range of scales, we observe that normal spontaneous walking has the highest complexity when compared to slow and fast walking and also to ...
Costa, M. +3 more
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Multiscale Renyi Entropy and Cardiac Autonomic Neuropathy
2015 20th International Conference on Control Systems and Computer Science, 2015Heart rate variability (HRV) is commonly analysed in respect to time and frequency domain measures as well as nonlinear measures including the fractal dimension using information derived from ECG recordings. Increased risk of adverse cardiac events such as arrhythmia can be detected using heart rate variability analysis.
Herbert F. Jelinek +3 more
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Relative entropy as a universal metric for multiscale errors
Physical Review E, 2010We show that the relative entropy, Srel, suggests a fundamental indicator of the success of multiscale studies, in which coarse-grained (CG) models are linked to first-principles (FP) ones. We demonstrate that Srel inherently measures fluctuations in the differences between CG and FP potential energy landscapes, and develop a theory that tightly and ...
Aviel, Chaimovich, M Scott, Shell
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Multiscale Entropy: Recent Advances
2017Multiscale entropy is a widely used metric for characterizing the complexity of physiological time series. The fundamental difference to classical entropy measures is it enables quantification of nonlinear dynamics underlying physiological processes over multiple time scales.
Meng Hu, Hualou Liang
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Multiscale entropy indicates vascular abnormalities in the aged
2011 International Conference on Machine Learning and Cybernetics, 2011This study investigates the feasibility and sensitivity of a novel multiscale entropy index (MEI) in detecting subtle endothelial dysfunction in young and middle-aged subjects. Between December 2009 and May 2010, totally 70 subjects were recruited from a hospital, and categorized into young group (Group 1), middle-aged or elderly group (Group 2 ...
Chun-Ho Lee +5 more
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Cardiac variability time-series analysis by sample entropy and multiscale entropy
International Journal of Medical Engineering and Informatics, 2015Ever since the use of heart rate variability (HRV) as a tool for quantification of autonomic nervous system dynamics has become popular, the interest in exploring the hidden complexities of physiologic time series has increased immensely. The sample entropy (SampEn) has been in use for quite some time as a complexity measure.
Puneeta Marwaha, Ramesh Kumar Sunkaria
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