Special Issue "Multiscale Entropy and Its Applications in Medicine and Biology"

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Entropy and Biology".

Deadline for manuscript submissions: closed (20 September 2015).

Special Issue Editor

Dr. Anne Humeau-Heurtier
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Guest Editor
Laboratoire Angevin de Recherche en Ingénierie des Systèmes (LARIS), University of Angers, IUT, GEII Department, 4 boulevard Lavoisier, BP 42018, 49016 Angers cedex, France
Interests: entropy; multiscale entropy; nonlinear analysis; empirical mode decomposition; biomedical data
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Special Issue Information

Dear Colleagues,

Multiscale entropy has been proposed to evaluate the complexity of time series by taking into account the multiple time scales in physical systems. For this purpose, the entropy values assigned to the time series under study are considered but the ones of the coarse-grained time series - that represent the system’s dynamics on different scales - are also analyzed. In biomedicine, multiscale entropy has risen as a complexity measure compatible with the unifying concept that healthy systems, regulated by various control mechanisms acting on multiple time scales, are more complex than pathologic ones for which such mechanisms are degraded. Multiscale entropy is, therefore, gaining many new applications in broad areas of medicine.

For this Special Issue of Entropy, we solicit contributions of new and original research on the concept of multiscale entropy and on the use of multiscale entropy in medicine and biology.

Dr. Anne Humeau-Heurtier
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (8 papers)

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Research

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Open AccessArticle
Using Wearable Accelerometers in a Community Service Context to Categorize Falling Behavior
Entropy 2016, 18(7), 257; https://doi.org/10.3390/e18070257 - 13 Jul 2016
Cited by 3
Abstract
In this paper, the Multiscale Entropy (MSE) analysis of acceleration data collected from a wearable inertial sensor was compared with other features reported in the literature to observe falling behavior from the acceleration data, and traditional clinical scales to evaluate falling behavior. We [...] Read more.
In this paper, the Multiscale Entropy (MSE) analysis of acceleration data collected from a wearable inertial sensor was compared with other features reported in the literature to observe falling behavior from the acceleration data, and traditional clinical scales to evaluate falling behavior. We use a fall risk assessment over a four-month period to examine >65 year old participants in a community service context using simple clinical tests, including the Short Form Berg Balance Scale (SFBBS), Timed Up and Go test (TUG), and the Short Portable Mental Status Questionnaire (SPMSQ), with wearable accelerometers for the TUG test. We classified participants into fallers and non-fallers to (1) compare the features extracted from the accelerometers and (2) categorize fall risk using statistics from TUG test results. Combined, TUG and SFBBS results revealed defining features were test time, Slope(A) and slope(B) in Sit(A)-to-stand(B), and range(A) and slope(B) in Stand(B)-to-sit(A). Of (1) SPMSQ; (2) TUG and SPMSQ; and (3) BBS and SPMSQ results, only range(A) in Stand(B)-to-sit(A) was a defining feature. From MSE indicators, we found that whether in the X, Y or Z direction, TUG, BBS, and the combined TUG and SFBBS are all distinguishable, showing that MSE can effectively classify participants in these clinical tests using behavioral actions. This study highlights the advantages of body-worn sensors as ordinary and low cost tools available outside the laboratory. The results indicated that MSE analysis of acceleration data can be used as an effective metric to categorize falling behavior of community-dwelling elderly. In addition to clinical application, (1) our approach requires no expert physical therapist, nurse, or doctor for evaluations and (2) fallers can be categorized irrespective of the critical value from clinical tests. Full article
(This article belongs to the Special Issue Multiscale Entropy and Its Applications in Medicine and Biology)
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Open AccessArticle
Wide Range Multiscale Entropy Changes through Development
Entropy 2016, 18(1), 12; https://doi.org/10.3390/e18010012 - 29 Dec 2015
Cited by 2
Abstract
How variability in the brain’s neurophysiologic signals evolves during development is important for a global, system-level understanding of brain maturation and its disturbance in neurodevelopmental disorders. In the current study, we use multiscale entropy (MSE), a measure that has been related to signal [...] Read more.
How variability in the brain’s neurophysiologic signals evolves during development is important for a global, system-level understanding of brain maturation and its disturbance in neurodevelopmental disorders. In the current study, we use multiscale entropy (MSE), a measure that has been related to signal complexity, to investigate how this variability evolves during development across a broad range of temporal scales. We computed MSE, standard deviation (STD) and standard spectral analyses on resting EEG from 188 healthy individuals aged 8–22 years old. We found age-related increases in entropy at lower scales (<~20 ms) and decreases in entropy at higher scales (~60–80 ms). Decreases in the overall signal STD were anticorrelated with entropy, especially in the lower scales, where regression analyses showed substantial covariation of observed changes. Our findings document for the first time the scale dependency of developmental changes from childhood to early adulthood, challenging a parsimonious MSE-based account of brain maturation along a unidimensional, complexity measure. At the level of analysis permitted by electroencephalography (EEG), MSE could capture critical spatiotemporal variations in the role of noise in the brain. However, interpretations critically rely on defining how signal STD affects MSE properties. Full article
(This article belongs to the Special Issue Multiscale Entropy and Its Applications in Medicine and Biology)
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Open AccessArticle
Multiscale Entropy Analysis on Human Operating Behavior
Entropy 2016, 18(1), 3; https://doi.org/10.3390/e18010003 - 22 Dec 2015
Cited by 5
Abstract
By exploiting the statistical analysis method, human dynamics provides new insights to the research of human behavior. In this paper, we analyze the characteristics of the computer operating behavior through a modified multiscale entropy algorithm with both the interval time series and the [...] Read more.
By exploiting the statistical analysis method, human dynamics provides new insights to the research of human behavior. In this paper, we analyze the characteristics of the computer operating behavior through a modified multiscale entropy algorithm with both the interval time series and the number series of individuals’ operating behavior been investigated. We also discuss the activity of individuals’ behavior from the three groups denoted as the retiree group, the student group and the worker group based on the nature of their jobs. We find that the operating behavior of the retiree group exhibits more complex dynamics than the other two groups and further present a reasonable explanation for this phenomenon. Our findings offer new insights for the further understanding of individual behavior at different time scales. Full article
(This article belongs to the Special Issue Multiscale Entropy and Its Applications in Medicine and Biology)
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Open AccessArticle
Multiscale Entropy Analysis of Surface Electromyographic Signals from the Urethral Sphincter as a Prognostic Indicator for Surgical Candidates with Primary Bladder Neck Obstruction
Entropy 2015, 17(12), 8089-8098; https://doi.org/10.3390/e17127863 - 08 Dec 2015
Cited by 2
Abstract
To explore information hidden in the electromyographic (EMG) signals of the urethral sphincter that may be of prognostic significance for patients with primary bladder neck obstruction (PBNO), 41 patients with voiding difficulty were divided into four groups: 1) patients with primary bladder neck [...] Read more.
To explore information hidden in the electromyographic (EMG) signals of the urethral sphincter that may be of prognostic significance for patients with primary bladder neck obstruction (PBNO), 41 patients with voiding difficulty were divided into four groups: 1) patients with primary bladder neck obstruction (PBNO) with successful (Group 1, n = 14) and 2) unsuccessful (Group 2, n = 8) surgical outcomes, 3) patients with detrusor overactivity (Group 3, n = 7), and 4) patients with detrusor-external sphincter dyssynergia (Group 4, n = 12). All patients underwent baseline urodynamic studies (preoperative for Group 1 and Group 2) for comparison. The results demonstrated that, despite no significant difference in urodynamic parameters between Group 1 and Group 2, the large-scale multiscale entropy (MSE) of preoperative EMG (i.e., MSELS(EMG)) of Group 1 was significantly higher than that of Group 2 without notable difference between Group 1 and Group 3 (i.e., patients with normal sphincter function). Moreover, the MSELS(EMG) and small-scale MSE of preoperative EMG (i.e., MSESS(EMG)) of Group 2 were notably higher than those of Group 4 (i.e., patients with abnormal sphincter function), while both MSELS(EMG) and MSESS(EMG) of Group 3 were notably higher than those of Group 2. In conclusion, using MSE analysis for assessing preoperative urethral sphincter EMG signals successfully distinguished between PBNO patients with subsequent successful surgery from those with surgical failure possibly due to subtle functional impairment of the urethral sphincter that cannot be detected by routine urodynamic studies. The results, therefore, highlight the potential clinical significance of this analytical tool in guiding urologists regarding their choice of medical versus surgical treatment for this patient population. Full article
(This article belongs to the Special Issue Multiscale Entropy and Its Applications in Medicine and Biology)
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Open AccessArticle
A Refined Multiscale Self-Entropy Approach for the Assessment of Cardiac Control Complexity: Application to Long QT Syndrome Type 1 Patients
Entropy 2015, 17(11), 7768-7785; https://doi.org/10.3390/e17117768 - 19 Nov 2015
Cited by 2
Abstract
The study proposes the contemporaneous assessment of conditional entropy (CE) and self-entropy (sE), being the two terms of the Shannon entropy (ShE) decomposition, as a function of the time scale via refined multiscale CE (RMSCE) and sE (RMSsE) with the aim at gaining [...] Read more.
The study proposes the contemporaneous assessment of conditional entropy (CE) and self-entropy (sE), being the two terms of the Shannon entropy (ShE) decomposition, as a function of the time scale via refined multiscale CE (RMSCE) and sE (RMSsE) with the aim at gaining insight into cardiac control in long QT syndrome type 1 (LQT1) patients featuring the KCNQ1-A341V mutation. CE was estimated via the corrected CE (CCE) and sE as the difference between the ShE and CCE. RMSCE and RMSsE were computed over the beat-to-beat series of heart period (HP) and QT interval derived from 24-hour Holter electrocardiographic recordings during daytime (DAY) and nighttime (NIGHT). LQT1 patients were subdivided into asymptomatic and symptomatic mutation carriers (AMCs and SMCs) according to the severity of symptoms and contrasted with non-mutation carriers (NMCs). We found that RMSCE and RMSsE carry non-redundant information, separate experimental conditions (i.e., DAY and NIGHT) within a given group and distinguish groups (i.e., NMC, AMC and SMC) assigned the experimental condition. Findings stress the importance of the joint evaluation of RMSCE and RMSsE over HP and QT variabilities to typify the state of the autonomic function and contribute to clarify differences between AMCs and SMCs. Full article
(This article belongs to the Special Issue Multiscale Entropy and Its Applications in Medicine and Biology)
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Open AccessArticle
Multi-Scale Entropy Analysis of Body Sway for Investigating Balance Ability During Exergame Play Under Different Parameter Settings
Entropy 2015, 17(11), 7608-7627; https://doi.org/10.3390/e17117608 - 04 Nov 2015
Cited by 2
Abstract
The goal of this study was to investigate the parameters affecting exergame performance using multi-scale entropy analysis, with the aim of informing the design of exergames for personalized balance training. Test subjects’ center of pressure (COP) displacement data were recorded during exergame play [...] Read more.
The goal of this study was to investigate the parameters affecting exergame performance using multi-scale entropy analysis, with the aim of informing the design of exergames for personalized balance training. Test subjects’ center of pressure (COP) displacement data were recorded during exergame play to examine their balance ability at varying difficulty levels of a balance-based exergame; the results of a multi-scale entropy-based analysis were then compared to traditional COP indicators. For games involving static posture frames, variation in posture frame travel time was found to significantly affect the complexity of both the anterior-posterior (MSE-AP) and medio-lateral (MSE-ML) components of balancing movements. However, in games involving dynamic posture frames, only MSE-AP was found to be sensitive to the variation of parameters, namely foot-lifting speed. Findings were comparable to the COP data published by Sun et al., indicating that the use of complexity data is a feasible means of distinguishing between different parameter sets and of understanding how human design considerations must be taken into account in exergame development. Not only can this method be used as another assessment index in the future, it can also be used in the optimization of parameters within the virtual environments of exergames. Full article
(This article belongs to the Special Issue Multiscale Entropy and Its Applications in Medicine and Biology)
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Review

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Open AccessReview
Multiscale Entropy Analysis of Center-of-Pressure Dynamics in Human Postural Control: Methodological Considerations
Entropy 2015, 17(12), 7926-7947; https://doi.org/10.3390/e17127849 - 30 Nov 2015
Cited by 25
Abstract
Multiscale entropy (MSE) is a widely used metric for characterizing the nonlinear dynamics of physiological processes. Significant variability, however, exists in the methodological approaches to MSE which may ultimately impact results and their interpretations. Using publications focused on balance-related center of pressure (COP) [...] Read more.
Multiscale entropy (MSE) is a widely used metric for characterizing the nonlinear dynamics of physiological processes. Significant variability, however, exists in the methodological approaches to MSE which may ultimately impact results and their interpretations. Using publications focused on balance-related center of pressure (COP) dynamics, we highlight sources of methodological heterogeneity that can impact study findings. Seventeen studies were systematically identified that employed MSE for characterizing COP displacement dynamics. We identified five key methodological procedures that varied significantly between studies: (1) data length; (2) frequencies of the COP dynamics analyzed; (3) sampling rate; (4) point matching tolerance and sequence length; and (5) filtering of displacement changes from drifts, fidgets, and shifts. We discuss strengths and limitations of the various approaches employed and supply flowcharts to assist in the decision making process regarding each of these procedures. Our guidelines are intended to more broadly inform the design and analysis of future studies employing MSE for continuous time series, such as COP. Full article
(This article belongs to the Special Issue Multiscale Entropy and Its Applications in Medicine and Biology)
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Open AccessReview
The Multiscale Entropy Algorithm and Its Variants: A Review
Entropy 2015, 17(5), 3110-3123; https://doi.org/10.3390/e17053110 - 12 May 2015
Cited by 107
Abstract
Multiscale entropy (MSE) analysis was introduced in the 2002 to evaluate the complexity of a time series by quantifying its entropy over a range of temporal scales. The algorithm has been successfully applied in different research fields. Since its introduction, a number of [...] Read more.
Multiscale entropy (MSE) analysis was introduced in the 2002 to evaluate the complexity of a time series by quantifying its entropy over a range of temporal scales. The algorithm has been successfully applied in different research fields. Since its introduction, a number of modifications and refinements have been proposed, some aimed at increasing the accuracy of the entropy estimates, others at exploring alternative coarse-graining procedures. In this review, we first describe the original MSE algorithm. Then, we review algorithms that have been introduced to improve the estimation of MSE. We also report a recent generalization of the method to higher moments. Full article
(This article belongs to the Special Issue Multiscale Entropy and Its Applications in Medicine and Biology)
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