Marcus Dunn

Kinetic and kinematic analysis of stamping impacts during simulated rucking in rugby union

ABSTRACT Laceration injuries account for up to 23% of injuries in rugby union. They are frequently caused by studded footwear as a result of a player stamping onto another player during the ruck. Little is known about the kinetics and kinematics of rugby stamping impacts; current test methods assessing laceration injury risk of stud designs therefore lack informed test parameters. In this study, twelve participants stamped on an anthropomorphic test device in a one-on-one simulated ruck setting. Velocity and inclination angle of the foot prior to impact was determined from high-speed video footage. Total stamping force and individual stud force were measured using pressure sensors. Mean foot inbound velocity was 4.3 m ∙ s−1 (range 2.1–6.3 m ∙ s−1). Mean peak total force was 1246 N and mean peak stud force was 214 N. The total mean effective mass during stamping was 6.6 kg (range: 1.6–13.5 kg) and stud effective mass was 1.2 kg (range: 0.5–2.9 kg). These results provide representative test parameters for mechanical test devices designed to assess laceration injury risk of studded footwear for rugby union.

Prevalence of laceration injuries in professional and amateur rugby union: a systematic review and meta-analysis

Background Studded footwear can cause severe lacerations in rugby union; the prevalence of these injuries is currently unknown. Objective To summarise the skin and laceration injury prevalence in published epidemiological studies and to investigate any differences in skin injury risk between amateur and professional players. Design Systematic literature review and meta-analysis of epidemiological studies. Data sources PubMed, Web of Science, Scopus and Ovid. Eligibility criteria for selecting studies Prospective, epidemiological studies published in English after 1995, measuring a minimum of 400 match or 900 training exposure hours. Participants should be adult rugby union players (amateur or professional). The study should report a separate skin or laceration injury category and provide sufficient detail to calculate injury prevalence within this category. Results Twelve studies were included. Mean skin injury prevalence during matches was 2.4 injuries per 1000 exposure hours; during training sessions, the prevalence was 0.06 injuries per 1000 exposure hours. Skin injuries accounted for 5.3% of match injuries and 1.7% of training injuries. Skin injury risk was similar for amateur compared with professional players during matches (OR: 0.63, p=0.46.), but higher during training sessions (OR: 9.24, p=0.02). Conclusions The skin injury prevalence of 2.4 injuries per 1000 exposure hours is equivalent to one time-loss injury sustained during matches per team, per season. Amateur players are more likely to sustain skin injuries during training sessions than professional players. There is a need for more studies observing injuries among amateur players. Trial registration number PROSPERO CRD42015024027.

Image Based Stroke-Rate Detection System for Swim Race Analysis

Swim race analysis systems often rely on manual digitization of recorded videos to obtain performance related metrics such as stroke-rate, stroke-length or swim velocity. Using image-processing algorithms, a stroke tagging system has been developed that can be used in competitive swimming environments. Test images from video footage of a women’s 200 m medley race recorded at the 2012 Olympic Games, was segmented into regions of interest (ROI) consisting of individual lanes. Analysis of ROI indicated that the red component of the RGB color map corresponded well with the splash generated by the swimmer. Detected red values from the splash were filtered and a sine-fitting function applied; the frequency of which was used to estimate stroke-rate. Results were compared to manually identified parameters and demonstrated excellent agreement for all four disciplines. Future developments will look to improve the accuracy of the identification of swimmer position allowing swim velocity to be calculated.

Effects of running retraining on biomechanical factors associated with lower limb injury

Injury risk is an important concern for runners; however, limited evidence exists regarding changes to injury risk following running style retraining. Biomechanical factors, such as absolute peak free moment, knee abduction impulse, peak foot eversion and foot eversion excursion, have been shown to predict lower limb injury. The aim of this study was to assess the effects of Pose running retraining on biomechanical factors associated with lower limb running injury. Twenty uninjured recreational runners were pair-matched based on their five km run time performance and randomly assigned to control (n = 10) and intervention (three 2-h Pose running retraining sessions) groups (n = 10). Three dimensional kinetic and kinematic data were collected from all participants running at relative (REL: 1.5 km·h-1 below respiratory compensation point) and absolute (ABS: 4.5 m·s-1) speeds. Biomechanical factors associated with lower limb injury, as well as selected kinematic variables (to aid interpretation), were assessed. Following a six-week, non-coached time-period, all assessments were repeated. No changes to the biomechanical factors associated with lower limb injury examined in this study were observed (P > .05). Intervention group participants (presented as pre- and post-intervention respectively) exhibited an increased foot strike index (REL speed: 21.79-42.66%; ESW = 4.73; P = .012 and ABS speed: 22.38-46.98%; ESW = 2.83; P = .008), reduced take-off distance (REL speed: -0.35 to -0.32 m; ESW = 0.75; P = .012), increased knee flexion at initial contact (REL speed: -14.11 to -18.50°; ESW = -0.88; P = .003), increased ankle dorsiflexion at terminal stance (REL speed: -33.61 to -28.35°; ESW = 1.57; P = .036) and reduced stance time (ABS speed: 0.21-0.19 s; ESW = -0.85; P = .018). Finally, five km run time did not change (22:04-22:19 min; ESW = 0.07; P = .229). It was concluded that following Pose running retraining, retrained participants adopted a running style that was different to their normal style without changing specific, biomechanical factors associated with lower limb injury or compromising performance.

Comparison of automated post-processing techniques for measurement of body surface area from 3D photonic scans

Body surface area (BSA) measurement is important in engineering and medicine fields to determine parameters for various applications. Three-dimensional scanning techniques may be used to acquire the BSA directly. Nevertheless, the raw data obtained from 3D scanning usually requires some manual post-processing which is time-consuming and requires technical expertise. Automated post-processing of 3D scans enables expedient BSA calculation with minimal technical expertise. The purpose of this research was to compare the accuracy and reliability of three different automated post-processing techniques including Stitched Puppet (SP), Poisson surface reconstruction (PSR), and screened Poisson surface reconstruction (SPSR) using manual post-processing as the criterion. Twenty-nine participants were scanned twice, and raw data were processed with the manual operation and automated techniques to acquire BSAs separately. The reliability of BSAs acquired from these approaches was represented by the relative technical error of measurements (TEM). Pearson’s regressions were applied to correct BSAs acquired from the automated techniques. The limits of agreement (LOA) were used to quantify the accuracy of BSAs acquired from the automated techniques and corrected by regression models. The reliability (relative TEM) of BSAs obtained from PSR, SPSR and SP were 0.32%, 0.30%, 0.82% respectively. After removing bias with the regression models, the LOA for PSR, SPSR and SP were (-0.0134 m2, 0.0135 m2), ±0.0131 m2, ±0.0573 m2 respectively. It is concluded that PSR and SPSR are good alternative approaches to manual post-processing for applications that need reliable and accurate measurements of BSAs with large populations.

Identifying representative test parameters to assess skin laceration injury risk for individual studs

Skin injuries account for ∼6% of all injuries in rugby union. Skin lacerations resulting from stud–skin interactions in rugby union are frequently caused by stamping in the ruck (Oudshoorn, Driscoll, Dunn, & James, 2016 Oudshoorn, B. Y., Driscoll, H. F., Dunn, M., & James, D. (2016). Procedia Engineering, 147, 496–500. [CrossRef], [Google Scholar] ). Stud design is regulated by World Rugbys Regulation 12, but no supporting evidence currently exists for the selected test parameters used in these standards. Ideally, mechanical tests that assess injury risk should replicate conditions observed during play (Ura & Carre, 2016 Ura, D., & Carre, M. (2016). Procedia Engineering, 147, 550–555. [CrossRef], [Google Scholar] ). Relevant mechanical test parameters, such as foot inbound velocity, stud impact energy, inclination angle and effective mass, can be derived through biomechanical analysis of rugby stamping. However, due to human movement variability, the measured kinetics and kinematics of stamping impacts can have a large range and replicating all possible parameters within a mechanical test device is unfeasible. Identifying different stamp techniques by clustering provides an economical solution.

Development of smart inner city recreational facilities to encourage active living

Lowfield Park in Sheffield, UK is a green recreational space maintained by the City Council. Lowfield Park was selected as the primary Sheffield FieldLab for the ProFit project which ended in 2015. The ProFit project was European Interreg IVbNWE funded with the aim of encouraging physical activity through innovations in products, services and ICT systems. In 2014 the Sheffield Hallam University City Athletics Stadium (SHUCAS) was introduced as a secondary FieldLab. A number of innovative systems have been installed into the FieldLabs, these include: Pan Tilt Zoom cameras, automatically timed sprint and running tracks, outdoor displays/touchscreen and a gait analyser. This paper describes the hardware, software and cloud infrastructure created to enable these systems. Pilot testing has been carried out over the last year and has found a positive effect on both sites. The systems created will be taken forward to Sheffield’s Olympic Legacy Park, which is currently under development.