Paralympic wheelchair athletes solely depend on the power of their upper-body for their on-court wheeled mobility as well as for performing sport-specific actions in ball sports, like a basketball shot or a tennis serve. The objective of WheelPower is to improve the power output of athletes in their sport-specific wheelchair to perform better in competition. To achieve this objective the current project systematically combines the three Dutch measurement innovations (WMPM, Esseda wheelchair ergometer, PitchPerfect system) to monitor a large population of athletes from different wheelchair sports resulting in optimal power production by wheelchair athletes during competition. The data will be directly implemented in feedback tools accessible to athletes, trainers and coaches which gives them the unique opportunity to adapt their training and wheelchair settings for optimal performance. Hence, the current consortium facilitates mass and focus by uniting scientists and all major Paralympic wheelchair sports to monitor the power output of many wheelchair athletes under field and lab conditions, which will be assisted by the best data science approach to this challenge.
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Purpose: Classification is a defining factor for competition in wheelchair sports, but it is a delicate and time-consuming process with often questionable validity. New inertial sensor-based measurement methods applied in match play and field tests allow for more precise and objective estimates of the impairment effect on wheelchair-mobility performance. The aim of the present research was to evaluate whether these measures could offer an alternative point of view for classification. Methods: Six standard wheelchair-mobility performance outcomes of different classification groups were measured in match play (n = 29), as well as best possible performance in a field test (n = 47). Results: In match results, a clear relationship between classification and performance level is shown, with increased performance outcomes in each adjacent higher-classification group. Three outcomes differed significantly between the low- and mid-classified groups, and 1, between the mid- and high-classified groups. In best performance (field test), there was a split between the low- and mid-classified groups (5 out of 6 outcomes differed significantly) but hardly any difference between the mid- and high-classified groups. This observed split was confirmed by cluster analysis, revealing the existence of only 2 performance-based clusters. Conclusions: The use of inertial sensor technology to obtain objective measures of wheelchair-mobility performance, combined with a standardized field test, produced alternative views for evidence-based classification. The results of this approach provide arguments for a reduced number of classes in wheelchair basketball. Future use of inertial sensors in match play and field testing could enhance evaluation of classification guidelines, as well as individual athlete performance. DOI: https://doi.org/10.1123/ijspp.2017-0326 LinkedIn: https://www.linkedin.com/in/rienkvdslikke/ https://www.linkedin.com/in/moniqueberger/ https://www.linkedin.com/in/annemarie-de-witte-9582b154/
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An important performance determinant in wheelchair sports is the power exchanged between the athletewheelchair combination and the environment, in short, mechanical power. Inertial measurement units (IMUs) might be used to estimate the exchanged mechanical power during wheelchair sports practice. However, to validly apply IMUs for mechanical power assessment in wheelchair sports, a well-founded and unambiguous theoretical framework is required that follows the dynamics of manual wheelchair propulsion. Therefore, this research has two goals. First, to present a theoretical framework that supports the use of IMUs to estimate power output via power balance equations. Second, to demonstrate the use of the IMU-based power estimates during wheelchair propulsion based on experimental data. Mechanical power during straight-line wheelchair propulsion on a treadmill was estimated using a wheel mounted IMU and was subsequently compared to optical motion capture data serving as a reference. IMU-based power was calculated from rolling resistance (estimated from drag tests) and change in kinetic energy (estimated using wheelchair velocity and wheelchair acceleration). The results reveal no significant difference between reference power values and the proposed IMU-based power (1.8% mean difference, N.S.). As the estimated rolling resistance shows a 0.9–1.7% underestimation, over time, IMU-based power will be slightly underestimated as well. To conclude, the theoretical framework and the resulting IMU model seems to provide acceptable estimates of mechanical power during straight-line wheelchair propulsion in wheelchair (sports) practice, and it is an important first step towards feasible power estimations in all wheelchair sports situations.
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