The use of physically constraining tools for grip-specific skill development in racket, stick and club sports: A scoping review.

Coaches use physically constraining tools to supplement their coaching when developing sport-specific skills, however, their effectiveness is unknown. This scoping review aimed to understand the efficacy of physically constraining tools used in racket, stick, and club sports for grip-specific skill development. This scoping review followed the Joanna Briggs Institute methodology and PRISMA guidelines. Peer-reviewed research, including quasi-experimental, true-experimental, case studies, and grey literature were considered. Peer-reviewed sources were searched on Web of Science, Medline, and SPORTDiscus until October 6th, 2022. Exclusion criteria were (1) not original peer-reviewed research; (2) disabled participants or used for rehabilitation; or (3) not available in English. Data extracted were the type of tool, research foci, measures, and outcomes of the tool's efficacy. Zero peer-reviewed sources were identified on the efficacy of using physically constraining tools for grip-specific skill development. Common trends identified from the excluded sources were explored to provide a basis for the importance of using physically constraining tools for grip-specific skill development. Many tools are used in coaching despite their unclear efficacy, however, the current results can guide future work to assess the acute and longitudinal effects of using these tools, specifically within the development and performance of sport-specific skills.

Modification and refinement of three-dimensional reconstruction to estimate body volume from a simulated single-camera image.

Objective: Body volumes (BV) are used for calculating body composition to perform obesity assessments. Conventional BV estimation techniques, such as underwater weighing, can be difficult to apply. Advanced machine learning techniques enable multiple obesity-related body measurements to be obtained using a single-camera image; however, the accuracy of BV calculated using these techniques is unknown. This study aims to adapt and evaluate a machine learning technique, synthetic training for real accurate pose and shape (STRAPS), to estimate BV. Methods: The machine learning technique, STRAPS, was applied to generate three-dimensional (3D) models from simulated two-dimensional (2D) images; these 3D models were then scaled with body stature and BV were estimated using regression models corrected for body mass. A commercial 3D scan dataset with a wide range of participants (n = 4318) was used to compare reference and estimated BV data. Results: The developed methods estimated BV with small relative standard errors of estimation (<7%) although performance varied when applied to different groups. The BV estimated for people with body mass index (BMI) < 30 kg/m2 (1.9% for males and 1.8% for females) were more accurate than for people with BMI ≥ 30 kg/m2 (6.9% for males and 2.4% for females). Conclusions: The developed method can be used for females and males with BMI < 30 kg/m2 in BV estimation and could be used for obesity assessments at home or clinic settings.

Effect of hurdling step strategy on the kinematics of the hurdle clearance technique.

Athletes use either an eight-step or a seven-step strategy to reach the first hurdle in the 110 m hurdles event. This study investigates the effect of step strategy on the hurdle clearance technique and spatio-temporal parameters of the four steps prior to hurdle clearance. Two-dimensional video data were collected in the sagittal plane from 12 male sprinters, grouped as seven-step (n = 6) or eight-step (n = 6) strategists. The take-off distance was 0.20 m further from the hurdle and the touchdown was 0.42 m closer to the hurdle for seven-step athletes. Additionally, seven-step athletes reduced the length of the final step before hurdle take-off by 0.14 m compared with the previous step, whereas the eight-step athletes extended their final step by 0.17 m. There was negligible difference between the mean horizontal velocities of the two groups throughout the hurdle clearance (0.02 m/s) or the approach time to the first hurdle from the block clearance (0.01 s). This presents an important first insight into the effect of the step strategy on the first hurdle kinematics. Our findings identify the take-off and touchdown distance parameters of the hurdle clearance technique, and approach step characteristics for a successful seven- or eight-step approach strategy to be employed.

Effect of hurdling step strategy on the kinematics of the block start.

Athletes use either a seven-step or eight-step strategy to reach the first hurdle in the 110 m hurdle event. This study investigated the effect of step strategy on the start position, the block exit and the first four approach steps. Two-dimensional video data were collected in the sagittal plane from 12 male sprinters, grouped as seven-step (n = 6) or eight-step (n = 6) strategists. Mean block spacing was 0.08 m further apart, block contact time 0.06s longer, first step 0.25 m longer and first ground contact 0.03s longer for seven-step athletes compared with eight-step athletes. There was also a greater vertical displacement of the centre of mass (CoM) (0.04 m) for the seven-step athletes compared with the eight-step athletes. Additionally, the front hip mean angular acceleration was 197°/s2 slower for the seven-step athletes than the eight-step athletes. There was limited difference between groups for mean horizontal velocity at the moment of block exit (0.14 m/s). These technical alterations provide an important first insight into start kinematics. The findings of this study identify the position in the starting blocks, and the key parameters which pertain to the initial phases for a successful seven-step approach strategy to be employed.

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.

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

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.