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Entropy Application in Biomechanics

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

Deadline for manuscript submissions: closed (30 September 2025) | Viewed by 875

Special Issue Editor

Department of Health Sciences and Kinesiology, Walter's College of Health Professions, Georgia Southern University, Statesboro, GA 30460, USA
Interests: biomechanics of human movement; aging; running injuries; gait analysis; the effects of specific pathologies on human movement (especially peripheral neuropathy, diabetes, and cerebral palsy)
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Special Issue Information

Dear Colleagues,

Many sport, locomotion, ergonomic, pathological, and other observable phenomena exhibit time evolution and can be successfully modeled via suitable mathematical expressions, usually in a set of differential equations. Because input–output relations between system quantities are generally non-proportional, associated dynamical behavior could be very complex or, under specific conditions, chaotic. Detection, description, analysis, quantification, and control of this random-like erratic motion associated with nonlinear dynamical systems is important due to universality (through dimensionless mathematical modeling) and several unique properties (sensitivity to initial conditions, mixing attractors, fractal dimension, long-term unpredictability, continuous frequency spectrum, etc.).

Besides its application in information theory, entropy is a general measure commonly used to analyze complex systems. Similarly to Lyapunov exponents or fractal dimensions, entropy describes the complexity of dynamics concerning system parameters, external forcing, initial conditions, or time instances.

Considering the recent advances in dynamic systems, we will continue to collate new ideas and describe promising methods arising from the field of analysis and modeling human behavior using complex nonlinear dynamical systems.

This Special Issue will accept original, unpublished papers and comprehensive reviews focused on (but not restricted to) the following research areas:

  • Application of different entropy calculations in biomechanical analysis of human movements.
  • Analysis of nonlinear dynamical systems with complex behavior.
  • New chaotic systems with unique properties, both autonomous and driven.
  • Experimental investigation of human movement with nonlinear dynamics.
  • Advanced computational algorithms applied in human movements.
  • Novel numerical methods dedicated to the quantitative analysis of dynamical human behaviors.
  • Algorithms for the analysis of time sequences and entropy calculation applied to human movements.

We look forward to your submissions.

Dr. Li Li
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 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.

Keywords

  • approximate entropy
  • balance
  • biomechanics
  • complexity
  • correlation entropy
  • electromyography
  • ergonomics
  • geometric entropy
  • Hilbert–Huang marginal spectrum entropy
  • injury risks
  • mobility (gait, walking, and running)
  • movement control
  • multiscale entropy
  • muscle contraction
  • nonlinear analysis
  • permutation entropy
  • postural control
  • sample entropy
  • Shannon entropy
  • sports
  • stability
  • variability

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Published Papers (1 paper)

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Research

12 pages, 585 KB  
Article
Effect of Running Speed on Gait Variability in Individuals with Functional Ankle Instability
by Wenhui Mao, Kanglong Zhao, Xiangguo Xu, Mengzi Sun, Kai Wang, Yilin Xu and Li Li
Entropy 2025, 27(11), 1131; https://doi.org/10.3390/e27111131 - 31 Oct 2025
Viewed by 516
Abstract
To compare lower limb joint angle variability between functional ankle instability (FAI) and healthy controls (CONs) at different running speeds using linear and nonlinear methods. Fifteen males with right-side FAI and fifteen matched CONs ran on a treadmill at self-selected, 20% faster, and [...] Read more.
To compare lower limb joint angle variability between functional ankle instability (FAI) and healthy controls (CONs) at different running speeds using linear and nonlinear methods. Fifteen males with right-side FAI and fifteen matched CONs ran on a treadmill at self-selected, 20% faster, and 20% slower speeds. From 25 gait cycles, the mean coefficient of variation (CV), Sample Entropy (SampEn), and largest Lyapunov Exponent (LyE) of hip, knee, and ankle angles were computed. A two-way (two groups × three speeds) mixed-design ANOVA was applied (α = 0.05). No significant interaction effects were observed. No significant differences were observed in the CV. SampEn showed group effects: FAI had lower values in hip horizontal, knee sagittal/coronal, and ankle coronal planes, but higher in the hip sagittal plane. Speed effects showed greater SampEn in the ankle sagittal and lower in the hip coronal plane at slow speed. LyE was reduced in FAI for hip, knee, and ankle sagittal planes. Speed effects indicated higher LyE in the knee sagittal and lower in the hip coronal plane at slow speed. FAI showed reduced variability, particularly in the sagittal plane, reflecting rigid control. Slower speeds increased ankle and knee sagittal variability but decreased hip coronal variability. Full article
(This article belongs to the Special Issue Entropy Application in Biomechanics)
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