Proceedings of the Institution of Mechanical Engineers,Part P: Journal of Sports Engineering and Technology

Using pressure transducers in soil surfaces prepared in controlled conditions, the vertical stress was recorded at 100 mm, 200 mm, and 350 mm depth within two soil surfaces of 1460 kg/m³ and 1590 kg/m³ for five subjects of 747–843 N body weight running at 4 m/s (5 per cent). Simultaneous in-shoe pressure data were collected to investigate the influence of soil density on loading experienced by the player and to provide information on the load applied to the surface. For each soil density, the subjects wore three different footwear types: soccer boots with traditional studs, boots with moulded studs, and boots designed for synthetic turf. For the mean of all subjects, there was no significant difference in the maximum vertical soil stress or loading rate between surfaces at any depth but within each surface there was a significant reduction of 32 kPa between –100 mm and the other depths. The peak loading rate was two orders of magnitude greater at –100 mm than at –200 mm or –350 mm. The variation in maximum vertical stress at –100 mm for different subjects was significant (p<0.001) and increased with increasing subject weight (R² = 0.87); at –200 mm and –350 mm there was no significant subject or density effect; a similar pattern was observed with the peak loading rate, with a linear relationship between the loading rate and the subject weight. In-shoe pressure data revealed no significant differences in the peak force or loading rate between surfaces, but a significantly lower heel pressure for the soft (1460 kg/m³) surface compared with the hard (1590 kg/m³) surface (p<0.05). Wearing of different footwear had no influence on the peak force or pressure but revealed a lower rate of loading of force for the moulded boot than for the studded boot when performing on the hard surface. There was a low and non-significant relationship between the peak input force and the peak force experienced within the surface (R² = 0.01; p > 0.05), however, peak resultant pressure data were used successfully to model the vertical stress distribution during running using a linear elastic model of soil behaviour. This novel approach to understanding the behaviour of the soil surface and the player has revealed a complex relationship between the input load and the load experienced by the surface. Future models will seek to understand this relationship further.

This paper presents a measurement-driven, musculoskeletal, full-body simulation model for biomechanical analysis of the double-poling (DP) technique in cross-country skiing. DP is a fast and powerful full-body movement; therefore, it is interesting to examine whether inverse dynamics using static optimization is working for a musculoskeletal full-body model with high accelerations, a large range of motion, and realistic loads. An experiment was carried out to measure motion and pole force of a skier on a double-poling ergometer. Using the measurement data, a simulation model was implemented in the AnyBody Modeling System (AnyBody Technology A/S, Denmark). Experimental results of motion and pole force from the DP ergometer, and also simulation results of relative muscle force profiles, are presented. These results agree with results found in literature when the kinematics and external kinetics are similar. Consequently, it should be possible to use computer simulations of this type for cross-country skiing simulations. With a simulation model, it is possible to perform optimization studies and to ask and answer ‘what if’ questions. Solutions to such problems are not easy to obtain by traditional testing alone.

In this study, grip force was measured during a standard golf tee shot using two different measurement techniques. The first utilized a matrix-type thin-film sensor applied to a golf grip, from which total grip force could be readily determined. The second method involved 31 individual thin-film force sensors strategically placed on two golf gloves, allowing the force output of specific regions of the hands to be measured. Twenty golfers of varying ability participated in each test. The discovery of a unique grip force ‘signature’ for each golfer emerged from these data. That is, each golfer had a very repeatable total grip force trace, but these traces varied considerably between golfers. High-speed video was also recorded for many of the golfers tested so that key phases in the swing could be identified on the force traces.

Over the past few years, there has been a significant change in the material used to construct softball bats. Since 2000, there has been a significant increase in the number of slow-pitch softball bats sold that are constructed entirely of composite-based materials. It is theorized that the introduction of these composite bats has resulted in an increase in batted-ball speed, which directly corresponds to a decrease in available pitcher reaction time and can lead to an increase in the risk of injury. To test this theory, a controlled field-test study was conducted using five different certified softball bat models and four experienced testers to quantify the performance of composite-based softball bats compared to a wooden softball bat. For the composite bats, the available pitcher reaction times varied from 0.390 to 0.365 s for a pitcher standing 15.24 m (50 ft) from the batter, while, for the wooden bat, the available pitcher reaction times varied from 0.452 to 0.419 s. This study demonstrates that composite-based slow-pitch softball bats perform at an unsafe level when the results are compared to published safety studies in the sports of softball and baseball, which advocate available pitcher reaction times of 0.409 to 0.420 s. In addition, possible mitigation methods are discussed that could make the sport of slow-pitch softball safer.

This study aimed to measure the magnitude of head impacts sustained by 14 male, youth (13 years old) ice hockey players wearing instrumented helmets, and to compare impacts across event type (practice, game), player position, and location. Head impact magnitudes were captured during 58 games and 51 practices. Mixed linear models were utilized to analyze differences by event type, player position, and location of impact. Game impact magnitudes were significantly greater than practice impacts. Impacts sustained by forwards were similar in magnitude to those sustained by defensemen. Significant differences between head impact locations across all player positions were observed. Impacts to the top of the head were significantly greater than impacts to the back, front, left, and right sides. Youth ice hockey players sustain helmet impacts nearing 20 g on average, similar to measured values in collegiate American football players, and of potential concern because this sample involves younger athletes. Future biomechanical studies are needed to better interpret the finding that there is an increased likelihood of higher magnitude head impacts to the top of the head. The authors' long-term goal is to improve the understanding of impacts that may lead to concussions in young athletes.

The devastating impact of obesity on global health is without question and it is generally agreed that low levels of physical activity, particularly sitting (i.e., sedentariness), are important in its pathogenesis. Therefore, the measure of physical activity such as walking is vital to its use in the research and clinical milieu.

This study investigated three accelerometry parameters (sampling rate, range, and data depth) on ten healthy subjects (BMI 18–31 kg/m²) walking on a calibrated treadmill at eight speeds (0, 0.95, 1.74, 2.48, 3.22, 4.04, 4.83, and 5.70 km/h) while wearing a three-axis accelerometer on the thigh (Crossbow Technology, San Jose, CA) in order to find an optimal system for the determination of walking speed, as well as a new data analysis strategy using a differentiation of the acceleration values (jerk). Twenty-four sampling rates (2–25 Hz in 1-Hz intervals) and seven acceleration ranges (± 1 g – ± 2.5 g at 0.25-g intervals) were used to create a 24 × 7 factorial design. Data was also truncated from two to seven digits in the mantissa.

This study found that although there is an improvement in walking speed prediction when sampling rate was set above 4 Hz (P<0.0002), there was no further improvement when the sampling rate is set higher. This study found that there is an increase in walking speed prediction accuracy when the range of acceleration is limited to ± 1 g (P<0.0024 for ± 2 g versus ± 1 g). This study found that increasing or decreasing data depth has no impact on walking speed prediction accuracy. Further, this study found that a model based on jerk was accurate at predicting walking speeds (r² 0.9 for all comparisons).

For measuring walking using a sensor on the thigh, there is no significant improvement gained by large sampling rates, data ranges, or data precision. A model based on the time rate of change of acceleration is a valid analysis tool for measuring walking.