Selecting the number of trials in experimental biomechanics studies

Experimental biomechanics studies often involve the comparison of mean values from individuals across two or more experimental conditions. The purpose of this study was to evaluate two existing methods for determining the number of trials necessary to estimate these means. The sequential estimation technique (SET) was investigated in terms of the influence of input data distribution on the outcome. Paired samples t-tests were investigated in terms of the interaction between the number of subjects and number of trials necessary to achieve an acceptable level of statistical power. Simulation models were developed to perform SET and paired samples t-tests on representative synthetic input data. The SET results confirmed that the number of trials to achieve a stable estimate of the mean is independent of the input distribution provided the mean and standard deviation are fixed. For the commonly used 20 reference trials and 0.25 standard deviation threshold 9 ± 8 trials were needed to achieve stability. The paired t-test results confirmed that both number of subjects and number of trials can have a marked effect on the statistical power, e.g. a power of 0.80 can be achieved for effect size of 0.80 using 15 subjects and at least 19 trials or 20+ subjects and only 3 trials. The SET method suffers from arbitrary convergence criteria and neglecting intra-subject variance and, thus, should be applied with extreme caution. In contrast, statistical power can provide a more objective and conclusive means for determining the number of trials required for a given experimental situation

A combined muscle model and wavelet approach to interpreting the surface EMG signals from maximal dynamic knee extensions

This study aimed to identify areas of reduced surface EMG amplitude and changed frequency across the phase space of a maximal dynamic knee extension task. The hypotheses were: (1) amplitude would be lower for eccentric contractions compared to concentric contractions and unaffected by fibre length; and (2) mean frequency would also be lower for eccentric contractions and unaffected by fibre length. Joint torque and EMG signals from the vastii and rectus femoris were recorded for eight athletic subjects performing maximum knee extensions at thirteen joint velocities spanning ±250° s–1. The instantaneous amplitude and mean frequency were calculated using the continuous wavelet transform time – frequency method, and the fibre dynamics were determined using a muscle model of the knee extensions. The results indicated: (1) only for the rectus femoris were amplitudes significantly lower for eccentric contractions (p = 0.019), for the vastii amplitudes during eccentric contractions were less than maximal, but this was also the case for concentric contractions due to a significant reduction in amplitude towards knee extension (p = 0.023); and (2) mean frequency increased significantly with decreasing fibre length for all knee extensors and contraction velocities (p = 0.029). Using time – frequency processing of the EMG signals and a muscle model allowed the simultaneous assessment of fibre length, velocity and EMG

Artificial grass: A conceptual model for degradation in performance

AbstractArtificial grass pitches (AGPs), with long fibres and sand and rubber infill, have seen growth within many sports at both professional and community levels. Academic research has tended to focus on athleticism, injuries and the development of equipment and test standards, while research and development for the turf, infill and shockpad layers has generally been undertaken by the manufacturers. This has led to an under researching and / or reporting of the factors influencing AGP degradation and the subsequent effects on pitch performance. Long term testing has shown that as rubber filled AGPs age their performance worsens; they generally become harder and play faster with ball roll often reported as one of the first standards to be affected. This paper presents a hypothesised model to describe the numerous factors causing degradation and their effects on performance. It is designed as a useful tool for research aimed at assessing and improving current maintenance operations which will ultimately lead to increasing the useful life of AGPs

Spatial and temporal analysis of surface hardness across a third-generation artificial turf pitch over a year

Despite the potentially negative effects on play performance and safety, little is currently known about the spatial and temporal variability in the properties of artificial turf pitches. The primary purpose of this study was to quantify the spatial and temporal variations in surface hardness across a 5-year-old third-generation artificial turf pitch over full year cycle. The secondary purpose was to investigate the key variables that contributed to these variations in surface hardness using a correlation approach. Surface hardness (2.25 kg Clegg impact hammer, average of drops 2-5), ground temperature and infill depth were measured at 91 locations across the third-generation artificial turf pitch in 13-monthly test sessions from August 2011 to August 2012 inclusive. For each month, rainfall in the 24 h prior to testing and pitch usage statistics were also obtained. Shockpad thickness was obtained from measurements taken when the carpet was replaced in 2007. Spatial and temporal variations were assessed using robust statistical measures while Spearman correlation was used to assess the contributions of the secondary variables to surface hardness variability. The results indicated that spatial variation in surface hardness exceeded temporal variation; the former demonstrated a median absolute deviation of 12 6 1 G across the pitch in any test session while the median absolute deviation for the latter was only 4 6 2 G across the 13 test sessions. Spatial variation in surface hardness was moderately correlated with shockpad thickness and weakly correlated with infill depth (both negative). These results reinforce the importance of monitoring spatial and temporal variations in play performance variables for third-generation surfaces as well as providing support for the role of maintenance in minimising the spatial variation

The effect of running velocity on footstrike angle - a curve-clustering approach

Despite a large number of studies that have considered footstrike pattern, relatively little is known about how runners alter their footstrike pattern with running velocity. The purpose of this study was to determine how footstrike pattern, defined by footstrike angle (FSA), is affected by running velocity in recreational athletes. One hundred and two recreational athletes ran on a treadmill at up to ten set velocities ranging from 2.2–6.1 m s−1. Footstrike angle (positive rearfoot strike, negative forefoot strike), as well as stride frequency, normalised stride length, ground contact time and duty factor, were obtained from sagittal plane high speed video captured at 240 Hz. A probabilistic curve-clustering method was applied to the FSA data of all participants. The curve-clustering analysis identified three distinct and approximately equally sized groups of behaviour: (1) small/negative FSA throughout; (2) large positive FSA at low velocities (≤4 m s−1) transitioning to a smaller FSA at higher velocities (≥5 m s−1); (3) large positive FSA throughout. As expected, stride frequency was higher, while normalised stride length, ground contact time and duty factor were all lower for Cluster 1 compared to Cluster 3 across all velocities; Cluster 2 typically displayed intermediate values. These three clusters of FSA – velocity behaviour, and in particular the two differing trends observed in runners with a large positive FSAs at lower velocities, can provide a novel and relevant means of grouping athletes for further assessment of their running biomechanics

Artificial turf research at Loughborough University

Research into artificial turf surfaces can be divided into the categories infrastructure, user safety and play performance. This paper discusses these three categories, presents current knowledge and appraises some remaining questions. A simple diagrammatic framework is proposed for describing and relating the fundamental components of sport surface related research. Infrastructure includes the design, construction, operation, and whole life costs associated with a facility. A key area for future research is to better understand maintenance and the benefits of various strategies / techniques. User safety, or injury risk, is a key concern for many stakeholders. Injury risk is a complex interaction of many factors related to the user, sport, equipment and environment. Whilst the introduction of an injury consensus in the late 1990s permitted much greater impact of studies in soccer and rugby, these have contributed little to understanding injury mechanisms. Furthermore, previous research is hampered with regard to the effect of the surface by utilizing simple mechanical tests that appear inappropriate to user activity, e.g. traction. Advancement of knowledge within this category demands better integration with play performance related measurements and research methods that support a more mechanistic approach. Play performance has been the focus of much recent research. For example, mechanical evaluation of surface systems in the laboratory / field, player testing with regard to player and surface response and perception of surface performance. There exists a real need to develop a ‘consensus’ in establishing suitable boundary conditions for both mechanical and player testing. This would help to identify the fundamental research questions related to play performance and allow improved comparison between research studies

Predicting maximum eccentric strength from surface EMG measurements

The origin of the well documented discrepancy between maximum voluntary and in vitro tetanic eccentric strength has yet to be fully understood. This study aimed to determine whether surface EMG measurements can be used to reproduce the in vitro tetanic force – velocity relationship from maximum voluntary contractions. Five subjects performed maximal knee extensions over a range of eccentric and concentric velocities on an isovelocity dynamometer whilst EMG from the quadriceps were recorded. Maximum voluntary (MVC) force – length – velocity data were estimated from the dynamometer measurements and a muscle model. Normalised amplitude – length – velocity data were obtained from the EMG signals. Dividing the MVC forces by the normalised amplitudes generated EMG corrected force – length – velocity data. The goodness of fit of the in vitro tetanic force – velocity function to the MVC and EMG corrected forces was assessed. Based on a number of comparative scores the in vitro tetanic force – velocity function provided a significantly better fit to the EMG corrected forces compared to the MVC forces (p ≤ 0.05), Furthermore, the EMG corrected forces generated realistic in vitro tetanic force – velocity profiles. A 58 ± 19% increase in maximum eccentric strength is theoretically achievable through eliminating neural factors. In conclusion, EMG amplitude can be used to estimate in vitro tetanic forces from maximal in vivo force measurements, supporting neural factors as the major contributor to the difference between in vitro and in vivo maximal force

Mechanical characterisation and strain rate sensitivity of rubber shockpad in 3G artificial turf

Artificial turf systems are increasingly prolific, and are typically comprised of multi-components. Their responses to interactions with users and equipment can be relatively complex under different loading conditions as they tend to be polymeric and elastomeric and hence can exhibit non-linear and strain rate dependent behaviour. To further study and better understand the behaviour of these systems, the development of a numerical model to accurately predict individual layers' behaviour as well as the overall system's response under different loading conditions is necessary. Such a model can be used to better optimise surface design such as material choices and layer thickness, also possibly reducing construction costs. The purpose of this study was to model the mechanical behaviour of the rubber shockpad layer used in 3G artificial turfs using finite element (FE) analyses. Shockpad layers in artificial turf play a vital role in the shock absorption and ball interactions, and affect user safety. The rubber shockpad used in this study was an elastic prefabricated mat comprised of recycled rubber shreds approximately 2 to 8 mm in size bonded with polyurethane. A series of 3D finite element dynamic analyses were carried out using ABAQUS applying compressive cyclic loading to simulate the shockpad behaviour under different loading frequencies. The frequencies were based on biomechanical data for an athlete walking, running and sprinting. Arruda-Boyce hyperelastic constitutive model was employed to best describe the stress-strain response of the rubber shockpad under compressive loading. A series of uniaxial compression tests were conducted and the results were employed to characterise the mechanical behaviour of the material. The best Arruda-Boyce's coefficients, for different strain rates were obtained using initial estimation (IEM) method and trial-and-error approach. The FE results showed the best-fit hyperelastic material model which can describe and predict the material behaviour under various strain rates. Finally, using finite element results a series of models were proposed to accurately predict the stress-strain behaviour of the material in different loading frequencies relevant to athlete