208 research outputs found
Zero- vs. one-dimensional, parametric vs. non-parametric, and confidence interval vs. hypothesis testing procedures in one-dimensional biomechanical trajectory analysis.
Biomechanical processes are often manifested as one-dimensional (1D) trajectories. It has been shown that 1D confidence intervals (CIs) are biased when based on 0D statistical procedures, and the non-parametric 1D bootstrap CI has emerged in the Biomechanics literature as a viable solution. The primary purpose of this paper was to clarify that, for 1D biomechanics datasets, the distinction between 0D and 1D methods is much more important than the distinction between parametric and non-parametric procedures. A secondary purpose was to demonstrate that a parametric equivalent to the 1D bootstrap exists in the form of a random field theory (RFT) correction for multiple comparisons. To emphasize these points we analyzed six datasets consisting of force and kinematic trajectories in one-sample, paired, two-sample and regression designs. Results showed, first, that the 1D bootstrap and other 1D non-parametric CIs were qualitatively identical to RFT CIs, and all were very different from 0D CIs. Second, 1D parametric and 1D non-parametric hypothesis testing results were qualitatively identical for all six datasets. Last, we highlight the limitations of 1D CIs by demonstrating that they are complex, design-dependent, and thus non-generalizable. These results suggest that (i) analyses of 1D data based on 0D models of randomness are generally biased unless one explicitly identifies 0D variables before the experiment, and (ii) parametric and non-parametric 1D hypothesis testing provide an unambiguous framework for analysis when one׳s hypothesis explicitly or implicitly pertains to whole 1D trajectories.JOURNAL OF BIOMECHANICS. 48(7):1277-1285 (2015)journal articl
Two-way ANOVA for scalar trajectories, with experimental evidence of non-phasic interactions
Kinematic and force trajectories are often normalized in time, with mean and variance summary statistic trajectories reported. It has been shown elsewhere, for simple one-factor experiments, that statistical testing can be conducted directly on those summary statistic trajectories using Random Field Theory (RFT). This technical note describes how RFT extends to two-factor designs, and how bizarre "non-phasic interactions" can occur in multi-factor experiments. We reanalyzed a public dataset detailing stance phase knee flexion during walking in (a) patellofemoral pain vs. controls, and (b) females vs. males using both a full model (with interaction effect) and a main-effects-only model. In both models the main effect of PAIN failed to reach significance at alpha=0.05. The main effect of GENDER reached significance over 5-40% stance (p=0.0005), but only for the full model. The interaction effect (in the full model) reached significance over 0-15% of stance (p=0.030), and resulted from greater flexion in females but decreased flexion in males in PFP vs. controls. Thus there was a non-phasic interaction in which a non-significant interaction (over 20-40% stance) suppressed the main effect of GENDER. Similarly, if we had only analyzed 20-40% stance, we would have committed Type II error by failing to reject the null PAIN-GENDER interaction hypothesis. The possible presence of non-phasic interactions implies that trajectory analyses must be conducted at the whole-trajectory level, because a failure to do so will generally miss non-phasic interactions if present. (C) 2014 Elsevier Ltd. All rights reserved.ArticleJOURNAL OF BIOMECHANICS. 48(1):186-189 (2015)journal articl
The reliability of data produced by isokinetic dynamometry (IKD) of knee extension and flexion movement
To investigate the feasibility of using isolated knee performance to measure the f-v profile of human muscle in vivo, we were using isokinetic dynamometry (IKD) technique that span the entire f-v profile of skeletal muscle. With institutional ethics approval, eleven healthy males (mean ± SD: age, 24.9 ± 3.1 years; body mass, 80.2 ± 10.1 kg; height, 176.2 ± 7.1 cm) completed this study. The participants were physically active and were familiarized with the techniques and protocol prior to completing 4 experimental sessions (1 introductory session and 3 repeated experiment sessions). The sessions was used a protocol of knee extensor function on IKD at isometric mode and angular velocities of 60˚.s-1, 120˚.s-1, 240˚.s-1 and 450˚.s-1. IKD data were not significantly different across the 3 repeated trials, demonstrating there was no evidence of systematic bias. The average coefficient of variation (CV) of IKD was 9.3 ± 3.0% ranging from 7.0 to 15.7%. Therefore the isolated knee performance to measure the f-v profile of human muscle in vivo using the IKD was feasible.Keywords: f-v profile, isokinetic dynamometry, skeletal muscl
Vector field statistical analysis of kinematic and force trajectories
When investigating the dynamics of three-dimensional multi-body biomechanical systems it is often difficult to derive spatiotemporally directed predictions regarding experimentally induced effects. A paradigm of 'non-directed' hypothesis testing has emerged in the literature as a result. Non-directed analyses typically consist of ad hoc scalar extraction, an approach which substantially simplifies the original, highly multivariate datasets (many time points, many vector components). This paper describes a commensurately multivariate method as an alternative to scalar extraction. The method, called 'statistical parametric mapping' (SPM), uses random field theory to objectively identify field regions which co-vary significantly with the experimental design. We compared SPM to scalar extraction by re-analyzing three publicly available datasets: 3D knee kinematics, a ten-muscle force system, and 3D ground reaction forces. Scalar extraction was found to bias the analyses of all three datasets by failing to consider sufficient portions of the dataset, and/or by failing to consider covariance amongst vector components. SPM overcame both problems by conducting hypothesis testing at the (massively multivariate) vector trajectory level, with random field corrections simultaneously accounting for temporal correlation and vector covariance. While SPM has been widely demonstrated to be effective for analyzing 3D scalar fields, the current results are the first to demonstrate its effectiveness for 1D vector field analysis. It was concluded that SPM offers a generalized, statistically comprehensive solution to scalar extraction's oversimplification of vector trajectories, thereby making it useful for objectively guiding analyses of complex biomechanical systems.ArticleJOURNAL OF BIOMECHANICS. 46(14):2394-2401 (2013)journal articl
DO MULTI-PLANAR ACL INJURY RISK VARIABLES RANK INDIVIDUALS MORE CONSISTENTLY ACROSS TASKS THAN UNI-PLANAR VARIABLES?
The ACL injury mechanism is multi-planar, yet rarely are multi-planar variables examined in an injury risk context. This study examines if multi-planar variables rank individuals more consistently across multiple tasks than uni-planar variables. Forty-four female athletes performed bilateral drop vertical jumps, single-leg hops, single-leg drop vertical jumps and sidestep tasks on their dominant leg. Uni-planar (KMab) and multi-planar (KMnsag) variables of the knee were extracted and correlated between tasks. Participants was ranked according to KMab and KMnsag, and then grouped into quintiles for each task. When variables are consistently ranked across tasks, a movement signature is identified. In total, uni-planar movement signatures were identified more than multi-planar movement signatures. However, both undesirable multi-planar and uni-planar movement signatures were identified in unique participants. Multi-planar and uni-planar variables are both important when screening for undesirable movements
HOW DO TENNIS PLAYERS CONTROL THEIR BALANCE DURING THE SERVE?
The purpose of this study was to investigate how postural balance is manifested in high level tennis players, and whether movement variability is phase dependent. Twelve experienced tennis players (8 males and 4 females; age 21.5±4.11 years; height 174.75±6.06 cm; body mass 66.83±8.12 kg) completed 10 tennis successful serves. Whole-body kinematics were recorded and whole-body extrapolated centre of mass trajectories calculated. Within-subject variation was presented temporally to evaluate phase-dependent differences. Overall, our results showed individual balance control preferences and a progressive increase of within-subject variability throughout the serve movement. This knowledge will help trainers and coaches identify learning and performance needs associated to whole-body balance control
ISBS 2022 CONFERENCE PROCEEDINGS TITLE AND FOREWARD
The ISBS is an international society totally dedicated to biomechanics in sports, whose primary purposes are: To provide a forum for the exchange of ideas for sports biomechanics researchers, coaches and teachers. To bridge the gap between researchers and practitioners. To gather and disseminate information and materials on biomechanics in sports.
Papers underwent a double blinded review process. Each paper in these proceedings has been reviewed by at least two members of the scientific committee
INITIAL EXPLORATIONS USING THE KNEE MOMENT VECTOR VERSUS THE KNEE ABDUCTION MOMENT TO IDENTIFY ATHLETES AT RISK OF ACL INJURY
The knee abduction moment (KM-Y) is a biomechanical risk factor for ACL injury, yet multi-planar loads are known to strain the ACL. The KM-Y alone is often used for injury screening and prediction. This study examined if the KM-Y alone would identify athletes with high knee moments. Forty five female participants performed a bilateral drop jump and single leg drop jump with each leg and their 3D motion characteristics and ground reaction forces were measured. The identification of “at risk” individuals was compared between KM-Y, the non-sagittal resultant moment and the resultant knee moment using a risk threshold of the mean+1.6SD. The KM-Y identified 60 and 70% athletes in each task whereas also using the non-sagittal resultant moment identified 90 and 100%. This suggests that transverse plane moments should not be ignored to identify at risk athletes
Childhood Cryptosporidiosis: A Case Report
Cryptosporidium has emerged as an important cause of diarrheal illness worldwide, especially amongst young children and patients with infectious or iatrogenic immune deficiencies. The authors describe a case of mild cryptosporidiosis in a well-nourished, immunocompetent, one-year-old child. Rapid clinical and parasitological improvement was observed after a 3-day course of nitazoxanide
PREDICTING GROUND REACTION FORCES FROM TRUNK KINEMATICS: A MASS-SPRING-DAMPER MODEL APPROACH
The purpose of this study was to explore if a mass-spring-damper model can simulate trunk kinematics during running with the purpose of predicting ground reaction forces (GRF). Vertical GRF and trunk kinematics was measured for 16 participants during running at 2-5 m·s-1. The vertical trunk acceleration were used to simulate the acceleration of a mass-spring-damper model’s upper mass and generate the eight model parameters required to predict GRF. Mean squared errors between 0.8 ± 0.4 and 0.9 ± 0.5 m·s-2 and between 19.1 ± 7.0 and 27.9 ± 14.5 N·kg-1 were observed for the trunk acceleration and GRF respectively. Despite excellent trunk acceleration simulations, poor GRF predictions indicated that a simple mass-spring-damper model is shortcoming to predict variations in distinct loading features across different running speeds
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