Exercise Physiology: Energy, Nutrition and Human Performance

https://digitalcommons.unomaha.edu/cgi/viewcontent.cgi?article=1079&context=biomechanicsarticles

Human movement variability, nonlinear dynamics, and pathology: Is there a connection?

Approximate entropy (ApEn) and sample entropy (SampEn) are mathematical algorithms created to measure the repeatability or predictability within a time series. Both algorithms are extremely sensitive to their input parameters: m (length of the data segment being compared), r (similarity criterion), and N (length of data). There is no established consensus on parameter selection in short data sets, especially for biological data. Therefore, the purpose of this research was to examine the robustness of these two entropy algorithms by exploring the effect of changing parameter values on short data sets. Data with known theoretical entropy qualities as well as experimental data from both healthy young and older adults was utilized. Our results demonstrate that both ApEn and SampEn are extremely sensitive to parameter choices, especially for very short data sets, N ≤ 200. We suggest using N larger than 200, an m of 2 and examine several r values before selecting your parameters. Extreme caution should be used when choosing parameters for experimental studies with both algorithms. Based on our current findings, it appears that SampEn is more reliable for short data sets. SampEn was less sensitive to changes in data length and demonstrated fewer problems with relative consistency.

/pdf/the-appropriate-use-of-approximate-entropy-and-sample-1dtlc2u1z8.pdf

The Appropriate Use of Approximate Entropy and Sample Entropy with Short Data Sets

Falling poses a major threat to the steadily growing population of the elderly in modern-day society. A major challenge in the prevention of falls is the identification of individuals who are at risk of falling owing to an unstable gait. At present, several methods are available for estimating gait stability, each with its own advantages and disadvantages. In this paper, we review the currently available measures: the maximum Lyapunov exponent (λS and λL), the maximum Floquet multiplier, variability measures, long-range correlations, extrapolated centre of mass, stabilizing and destabilizing forces, foot placement estimator, gait sensitivity norm and maximum allowable perturbation. We explain what these measures represent and how they are calculated, and we assess their validity, divided up into construct validity, predictive validity in simple models, convergent validity in experimental studies, and predictive validity in observational studies. We conclude that (i) the validity of variability measures and λS is best supported across all levels, (ii) the maximum Floquet multiplier and λL have good construct validity, but negative predictive validity in models, negative convergent validity and (for λL) negative predictive validity in observational studies, (iii) long-range correlations lack construct validity and predictive validity in models and have negative convergent validity, and (iv) measures derived from perturbation experiments have good construct validity, but data are lacking on convergent validity in experimental studies and predictive validity in observational studies. In closing, directions for future research on dynamic gait stability are discussed.

/pdf/assessing-the-stability-of-human-locomotion-a-review-of-2k18qbw2kd.pdf

Assessing the stability of human locomotion: a review of current measures

This paper overviews the importance for sports biomechanics of movement variability, which has been studied for some time by cognitive and ecological motor skills specialists but, until quite recently, had somewhat been overlooked by sports biomechanists. The paper considers biomechanics research reporting inter- and intra-individual movement variability in javelin and discus throwing, basketball shooting, and locomotion. The overview does not claim to be comprehensive and we exclude such issues as the theoretical background to movement and coordination variability and their measurement. We overview evidence, both theoretical and empirical, of inter-individual movement variability in seeking to achieve the same task goal, in contrast to the concept of “optimal” movement patterns. Furthermore, even elite athletes cannot reproduce identical movement patterns after many years of training, contradicting the ideas of motor invariance and “representative” trials. We contend that movement variability, far from b...

/pdf/is-movement-variability-important-for-sports-biomechanists-3hsy5ls8l0.pdf

Is movement variability important for sports biomechanists

Variability is a critical aspect of a dynamical systems analysis. Because there are a number of numerical techniques that can be used in such an analysis, the calculation of variability has several issues that must be addressed. The purpose of this paper is to present a variety of quantitative methods for investigating variability from a dynamical systems perspective. The paper is divided into two major sections covering discrete and continuous methods. Each of these sections is subdivided into two sections. Within discrete methods, we discuss, first, the calculation of the discrete relative phase from a time-series history of two parameters and, second, the use of return maps. Using continuous methods, we present procedures for using angle-angle plots in the evaluation of relative phase. We then discuss the use of phase plots in the calculation of the continuous relative phase. Each of these methods presents unique problems for the researcher and the method to be used is determined by the nature of the question asked.

/pdf/issues-in-quantifying-variability-from-a-dynamical-systems-316if137gg.pdf

Issues in Quantifying Variability From a Dynamical Systems Perspective

Adaptations in interlimb and intralimb coordination to asymmetrical loading in human walking.

http://people.umass.edu/jhamill/PDF/Peters%20et%20al.,%202003.pdf

Limitations in the use and interpretation of continuous relative phase.

Continuous relative phase (CRP), a variable used to quantify intersegmental coordination, is difficult to interpret if care is not taken regarding the assumptions and limitations of the measure. Specifically, CRP is often interpreted as a higher resolution form of discrete relative phase (DRP). DRP, however, yields information regarding the relative dispersion of events in oscillatory signals while CRP describes their relationship in a higher order phase-plane domain. In this paper we address issues surrounding the calculation of CRP and suggest a new interpretation based on the aforementioned methodological issues. Through the use of test signals, with known properties, it was found that the CRP information will be arbitrary if no normalization procedures are used to account for frequency differences in the component oscillators. In addition, signals with non-sinusoidal trajectories will produce patterns in CRP that are not equivalent to discrete relative phase (DRP) measures. The implications of these issues are discussed. r 2002 Elsevier Science Ltd. All rights reserved.

Jeffrey M. Haddad

Papers

Issues in Quantifying Variability From a Dynamical Systems Perspective

Adaptations in interlimb and intralimb coordination to asymmetrical loading in human walking.

Limitations in the use and interpretation of continuous relative phase.

Short communication Limitations in the use and interpretation of continuous relative phase

Age-related changes in upper body adaptation to walking speed in human locomotion