The nature of functional variability in plantar pressure during a range of controlled walking speeds

During walking, variability in step parameters allows the body to adapt to changes in substrate or unexpected perturbations that may occur as the feet interface with the environment. Despite a rich literature describing biomechanical variability in step parameters, there are as yet no studies that consider variability at the body–environment interface. Here, we used pedobarographic statistical parametric mapping (pSPM) and two standard measures of variability, mean square error (m.s.e.) and the coefficient of variation (CV), to assess the magnitude and spatial variability in plantar pressure across a range of controlled walking speeds. Results by reduced major axis, and pSPM regression, revealed no consistent linear relationship between m.s.e. and speed or m.s.e. and Froude number. A positive linear relationship, however, was found between CV and walking speed and CV and Froude number. The spatial distribution of variability was highly disparate when assessed by m.s.e. and CV: relatively high variability was consistently confined to the medial and lateral forefoot when measured by m.s.e., while the forefoot and heel show high variability when measured by CV. In absolute terms, variability by CV was universally low (less than 2.5%). From these results, we determined that variability as assessed by m.s.e. is independent of speed, but dependent on speed when assessed by CV

On the thermodynamic origin of metabolic scaling

This work has been funded by projects AYA2013-48623-C2-2, FIS2013-41057-P, CGL2013-46862-C2-1-P and SAF2015-65878-R from the Spanish Ministerio de Economa y Competitividad and PrometeoII/2014/086, PrometeoII/2014/060 and PrometeoII/2014/065 from the Generalitat Valenciana (Spain). BL acknowledges funding from a Salvador de Madariaga fellowship, and L.L. acknowledges funding from EPSRC Early Career fellowship EP/P01660X/1

Team sports performance analysed through the lens of social network theory: implications for research and practice

This paper discusses how social network analyses and graph theory can be implemented in team sports performance analyses to evaluate individual (micro) and collective (macro) performance data, and how to use this information for designing practice tasks. Moreover, we briefly outline possible limitations of social network studies and provide suggestions for future research. Instead of cataloguing discrete events or player actions, it has been argued that researchers need to consider the synergistic interpersonal processes emerging between teammates in competitive performance environments. Theoretical assumptions on team coordination prompted the emergence of innovative, theoretically-driven methods for assessing collective team sport behaviours. Here, we contribute to this theoretical and practical debate by conceptualising sports teams as complex social networks. From this perspective, players are viewed as network nodes, connected through relevant information variables (e.g., a ball passing action), sustaining complex patterns of interaction between teammates (e.g., a ball passing network). Specialized tools and metrics related to graph theory could be applied to evaluate structural and topological properties of interpersonal interactions of teammates, complementing more traditional analysis methods. This innovative methodology moves beyond use of common notation analysis methods, providing a richer understanding of the complexity of interpersonal interactions sustaining collective team sports performance. The proposed approach provides practical applications for coaches, performance analysts, practitioners and researchers by establishing social network analyses as a useful approach for capturing the emergent properties of interactions between players in sports teams

Systematic Evaluation of the Descriptive and Predictive Performance of Paediatric Morphine Population Models

Purpose: A framework for the evaluation of paediatric population models is proposed and applied to two different paediatric population pharmacokinetic models for morphine. One covariate model was based on a systematic covariate analysis, the other on fixed allometric scaling principles. Methods: The six evaluation criteria in the framework were 1) number of parameters and condition number, 2) numerical diagnostics, 3) prediction-based diagnostics, 4) η-shrinkage, 5) simulation-based diagnostics, 6) diagnostics of individual and population parameter estimates versus covariates, including measurements of bias and precision of the population values compared to the observed individual values. The framework entails both an internal and external model evaluation procedure. Results: The application of the framework to the two models resulted in the detection of overparameterization and misleading diagnostics based on individual predictions caused by high shrinkage. The diagnostic of individual and population parameter estimates versus covariates proved to be highly informative in assessing obtained covariate relationships. Based on the framework, the systematic covariate model proved to be superior over the fixed allometric model in terms of predictive performance. Conclusions: The proposed framework is suitable for the evaluation of paediatric (covariate) models and should be applied to corroborate the descriptive and predictive properties of these models

Emergence of contact injuries in invasion team sports : an ecological dynamics rationale

The incidence of contact injuries in team sports is considerable, and injury mechanisms need to be comprehensively understood to facilitate the adoption of preventive measures. In Association Football, evidence shows that the highest prevalence of contact injuries emerges in one-on-one interactions. However, previous studies have tended to operationally report injury mechanisms in isolation, failing to provide a theoretical rationale to explain how injuries might emerge from interactions between opposing players. In this position paper, we propose an ecological dynamics framework to enhance current understanding of behavioural processes leading to contact injuries in team sports. Based on previous research highlighting the dynamics of performer–environment interactions, contact injuries are proposed to emerge from symmetry-breaking processes during on-field interpersonal interactions among competing players and the ball. Central to this approach is consideration of candidate control parameters that may provide insights on the information sources used by players to reduce risk of contact injuries during performance. Clinically, an ecological dynamics analysis could allow sport practitioners to design training sessions based on selected parameter threshold values as primary and/or secondary preventing measures during training and rehabilitation sessions

Sizing Up Allometric Scaling Theory

Metabolic rate, heart rate, lifespan, and many other physiological properties vary with body mass in systematic and interrelated ways. Present empirical data suggest that these scaling relationships take the form of power laws with exponents that are simple multiples of one quarter. A compelling explanation of this observation was put forward a decade ago by West, Brown, and Enquist (WBE). Their framework elucidates the link between metabolic rate and body mass by focusing on the dynamics and structure of resource distribution networks—the cardiovascular system in the case of mammals. Within this framework the WBE model is based on eight assumptions from which it derives the well-known observed scaling exponent of 3/4. In this paper we clarify that this result only holds in the limit of infinite network size (body mass) and that the actual exponent predicted by the model depends on the sizes of the organisms being studied. Failure to clarify and to explore the nature of this approximation has led to debates about the WBE model that were at cross purposes. We compute analytical expressions for the finite-size corrections to the 3/4 exponent, resulting in a spectrum of scaling exponents as a function of absolute network size. When accounting for these corrections over a size range spanning the eight orders of magnitude observed in mammals, the WBE model predicts a scaling exponent of 0.81, seemingly at odds with data. We then proceed to study the sensitivity of the scaling exponent with respect to variations in several assumptions that underlie the WBE model, always in the context of finite-size corrections. Here too, the trends we derive from the model seem at odds with trends detectable in empirical data. Our work illustrates the utility of the WBE framework in reasoning about allometric scaling, while at the same time suggesting that the current canonical model may need amendments to bring its predictions fully in line with available datasets

The relationship between objectively measured attributes of the built environment and selected cardiovascular risk factors in a South African urban setting

BACKGROUND: Evidence concerning the relationship between objectively-measured attributes of the built environment with cardio-metabolic risk in populations from lower- and middle-income countries is lacking. In this paper, we describe the association between the objectively-measured built environment with body mass index, blood pressure and physical activity in adult South Africans. METHODS: This cross-sectional study included 341 adults aged ≥35 years drawn from the Cape Town arm of the Prospective Urban Rural Epidemiology (PURE) cohort study. All Cape Town PURE participants were invited to take part in the study. Actigraph GT3X accelerometer and Geographic Information Systems were used to measure physical activity and built environment attributes (community center, shopping center and taxi rank). RESULTS: In age and sex adjusted models (reference 500 m), access to community centers (1000 m) was positively related to body mass index [beta 4.70 (95%CI: 2.06 to 7.34)] and diastolic blood pressure [4.97 (0.00 to 9.95)]. Distance from a community center (1600 m) was positively related to diastolic blood pressure [6.58 (1.57 to 11.58)] and inversely with moderate-to-vigorous physical activity [− 69.30 (− 134.92 to − 3.70)]. Distance to a shopping center (1600 m) was positively related to body mass index [4.78 (1.11 to 8.45)] and shopping center (1000 m) was positively related to systolic blood pressure respectively [76.99 (0.03 to 83.95)]. CONCLUSION: Distance to community and shopping centers were significantly associated with BMI, systolic, diastolic blood pressure and moderate-to-vigorous physical activity. Future research should include multiple aspects of built environment variables in order to provide for a broader understanding of their effect on cardiovascular risk profile of African populations