Nowadays, technology in sport plays an important role to help training and judgement processes. This study proposes the use of a wearable inertial system to derive novel biomechanical indices for the assessment of performance and infringements in race-walking. These indices are built from five inertial-based parameters: loss of ground contact time, loss of ground contact step classification, step length ratio, step cadence and smoothness. The biomechanical indices are customized for elite race-walkers, and represented on a radar chart for an intuitive analysis of performance and infringements. From the radar chart, a synthetic index regarding the athlete’s overall gesture is derived. The validation of the biomechanical indices is carried out in field tests, involving nine elite race-walkers wearing an inertial sensor located at the end of the column vertebra (L5–S1). A statistical analysis is used to determinate the quality and reliability of the proposed indices and of their representation. The results show that these biomechanical indices can be implemented on a wearable inertial system for assistance in training and judgement in race-walking.

The hand-wrist region is reported as the most common injury site in boxing. Boxers are at risk due to the amount of wrist motions when impacting training equipment or their opponents, yet we know relatively little about these motions. This paper describes a new method for quantifying wrist motion in boxing using an electromagnetic tracking system. Surrogate testing procedure utilising a polyamide hand and forearm shape, and in vivo testing procedure utilising 29 elite boxers, were used to assess the accuracy and repeatability of the system. 2D kinematic analysis was used to calculate wrist angles using photogrammetry, whilst the data from the electromagnetic tracking system was processed with visual 3D software. The electromagnetic tracking system agreed with the video-based system (paired t tests) in both the surrogate (< 0.2°) and quasi-static testing (< 6°). Both systems showed a good intraclass coefficient of reliability (ICCs > 0.9). In the punch testing, for both repeated jab and hook shots, the electromagnetic tracking system showed good reliability (ICCs > 0.8) and substantial reliability (ICCs > 0.6) for flexion–extension and radial-ulnar deviation angles, respectively. The results indicate that wrist kinematics during punching activities can be measured using an electromagnetic tracking system.

When dealing with full suspension mountain bikes, pedal kickback is one of the main parameters used to assess the performance of rear wheel kinematics. According to the currently used theory of Kovacs, pedal kickback is the backwards rotation of the crank during the compression of the rear suspension, which mainly occurs because of elongation between the bottom bracket and the rear axle. Most bike companies try to minimize pedal kickback during kinematic design, because this phenomenon creates unwanted harshness in the suspension and negatively influences rider stability due to the backwards rotation of the crank. When riding downhill above a certain velocity (i.e., the critical velocity) without pedaling or blocking the rear wheel, the cassette will complete a forward rotation instead of a backwards rotation of the crank, which is hereinafter referred to as freewheel theory. The cassette will perform this forward rotation without affecting the rider or creating suspension harshness. The paper discusses the analytical derivation for the calculation of the linearized critical velocity and presents a multibody simulation to calculate the exact critical velocity. The existence of the critical velocity is shown through measurements with an instrumented bike during a test ride on a downhill track and through an experiment performed under idealized conditions. The test ride demonstrated the influence of the rider on the critical velocity by moving the cranks in certain riding situations, such as landing on the front wheel first or hitting large obstacles. The crank movement leads to an increased (forward rotation) or decreased (backwards rotation) critical velocity. Both riding situations are reproduced with the multibody simulation.

The intricate physical interaction between the golfer and golf club has driven the development of numerous dynamic golf swing models over the past few decades. Within these golf swing models, the shaft is represented analytically, and simplifications are often made to strike a balance between the demanding computation required for simulating full swings and running optimizations. Despite recent progress in modeling golfer biomechanics, there has been a marked lack of experimental validation surrounding the dynamic behaviour of the analytical shaft models used in golf swing simulations. The purpose of this study was to evaluate the simulated behaviour of an advanced, continuously-parameterized analytical golf shaft model using experimental data collected in constrained mechanical property experiments as well as golf swing motion capture experiments. In the constrained experiments, the model predicted the experimental shaft’s static deflection and bending frequency within a relative error of 1%. In simulations of full swings, the model authentically replicated the unique bending patterns for each of the 20 golfers in the motion capture experiment. The root mean square errors for the shaft droop, lag, and twist angles for all swings ($$N=200$$) were $$1.14^{\circ }$$, $$0.83^{\circ }$$, and $$0.85^{\circ }$$, respectively, and the clubhead speed at the time of impact was predicted to within $$-\,2.9$$ to 0.6%. Empowered by symbolic computation, the model is computationally efficient enough for fast simulations of full swings ($$<1$$ s CPU time) on a desktop computer, thereby enabling golf shaft design optimization.

A new measurement system (horizontal displacement, time of flight, synchronicity—HDTS) was investigated regarding the latest changes to the international evaluation rules in trampoline gymnastics. It allows for the real-time measurement of objective criteria, such as flight time and landing position, without affecting the gymnast. The aim of this study was to investigate the temporal and spatial accuracy of a measurement tool via cross-validation. Temporal precision was additionally tested via high-speed video landing and takeoff, while a three-dimensional motion capturing system was incorporated for spatial precision. The Bland–Altman “limit of agreement approach” was used for the assessment of congruence between the measurement systems. The new measurement system presented an average spatial deviation of 3.2 cm and a temporal deviation between − 5.8 and + 6.4 ms for the landing and − 11.3 and + 11.3 ms for the takeoff. Given its temporal and spatial accuracy in determining flight time and landing position as identified through cross-validation, the novel HDTS system proved to be suitable for its use in trampoline competitions.

A single isolated ski was suspended from a six-component wind tunnel balance and three angles, the angle of attack, the yaw angle and the edge angle were adjustable during the test. Increasing yaw angle from 0 to 15° increased the lift coefficient CL from 0.42 to 0.90 at edge angle 0° and from 0.70 to 0.87 at edge angle 10°, respectively. Increasing yaw angle also increased the sensitivity of the ski to changes in edge angle, i.e., increasing the edge angle (20°–45°) decreased the CL and the ratio C_{L}^{2}/{C_D} with large yaw angles. However, to maximize the lift-to-drag ratio with a typical angle of attack of 30° in ski jumping, it may be reasonable to have an edge angle of 5°–10° on skis as the ratio C_{L}^{2}/{C_D} increased from 1.24 to 1.35 when edge angle increased from 0° to 10°.

Touch/control football boots are reportedly designed for optimal passing and dribbling. Little research exists on the effect of boot design on touch/control performance and no validated protocol has been developed for assessing passing and dribbling from an equipment focus. This study aimed to assess the effect of upper padding on dribbling and passing performance using a test–retest reliable test setup. Eight university players performed a protocol of dribbling, short and long passing in football boots with 0 and 6 mm of upper padding (Poron foam). The protocol was completed twice; the 0-mm padding results were used for test–retest validation, while the 0-mm versus 6-mm padding results were used to investigate the effect of padding. Dribbling performance was assessed though completion time, number of touches applied and lateral deviation from cones and passing performance through ball velocity and offset from target. The protocol demonstrated good test–retest reliability and indicated no significant differences in any of the 12 performance variables between the 0- and 6-mm padded boots. These findings suggest an element of design freedom in the use of padding within football boot uppers without affecting dribbling or passing performance.

The purpose of this research was to propose a method to acquire the three-dimensional movement of a roller skiing athlete utilizing a global positioning system (GPS), an atmospheric pressure sensor (APS), and an inertial measurement unit (IMU) to distinguish between diagonal skiing and double poling techniques. In this study, we developed a lightweight wearable sensor that was composed of a GPS, APS, and IMU. For the data collection, two national level athletes roller skied a 1700 m long course where the maximum difference in elevation was 5.3 m. The planar positions of the athletes were based on the longitudinal and latitudinal data provided by the GPS, and the altitude was calculated by the International barometric formula and Laplace transform from the APS. The longitudinal and latitudinal data acquired through GPS had errors within 2 m range at each point. The altitude of Laplace transform from the APS showed errors of less than 1 m at each point. The range of motion of pelvis from the IMU was 34.0 ± 3.8° for diagonal skiing, which is wider than the 21.2 ± 6.9° for double poling.

A robust method of quantifying athlete movement and pressure distribution across the seating interface of wheelchair athletes is required for athlete monitoring, optimising athlete performance, and computational simulations. The purpose of this study was to investigate whether a pressure mat is capable of measuring the distribution of pressure during wheelchair sport motion, and analyse the relationship between an athlete’s pressure distribution and their movement at the seating interface. Pressure was measured at the seating interface (wheelchair racing, n = 6, wheelchair rugby, n = 2) under conditions of steady state (racing athletes only), acceleration from stationary (racing and rugby), and agility (rugby only). All athletes demonstrated large within-trial variation in average pressure, peak pressure, and contact area for the acceleration and agility (rugby only) trials, suggesting the change in requirements of the seating interface for wheelchair athletes across different motions. This research suggests the need for greater individualisation of athlete–wheelchair seating interfaces to promote performance, as well as the importance of including these seating interactions in biomechanical analyses of wheelchair propulsion. Regular monitoring of pressure distribution and sport specific demands will assist in wheelchair prescription and provide improved understanding of individual seat design requirements associated with specific athlete impairments.

An inertial measurement unit (IMU) is widely considered to be an economical alternative to capture human motion in daily activities. Use of an IMU for clinical study, rehabilitation, and in the design of orthoses and prostheses has increased tremendously. However, its use in defining running gait is limited. This study presents a practical method to estimate running spatial and temporal parameters using an inertial sensor by placing it on a shoe. A combination of a zero-crossing method and thresholding is used to identify foot-strike and foot-off based on foot acceleration during running. Stride time, ground contact time and flight time can then be identified. An off-phase segmentation algorithm is applied to estimate stride length and running speed. These two parameters are commonly used to evaluate running efficiency and to differentiate elite runners. This study found that an IMU can estimate foot-strike and foot-off with average absolute time differences of 2.60–6.04 and 2.61–16.28 ms, respectively. Stride time was estimated with error between − 4.04 and 0.33 ms. Stride length and running speed were estimated with maximum average errors of 45.97 mm and 0.41 km/h.