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Kinematics and kinetics of handcycling propulsion at increasing workloads in able-bodied subjects
(2018)
In Paralympic sports, biomechanical optimisation of movements and equipment seems to be promising for improving performance. In handcycling, information about the biomechanics of this sport is mainly provided by case studies. The aim of the current study was (1) to examine changes in handcycling propulsion kinematics and kinetics due to increasing workloads and (2) identify parameters that are associated with peak aerobic performance. Twelve non-disabled male competitive triathletes without handcycling experience voluntarily participated in the study. They performed an initial familiarisation protocol and incremental step test until exhaustion in a recumbent racing handcycle that was attached to an ergometer. During the incremental test, tangential crank kinetics, 3D joint kinematics, blood lactate and ratings of perceived exertion (local and global) were identified. As a performance criterion, the maximal power output during the step test (Pmax) was calculated and correlated with biomechanical parameters. For higher workloads, an increase in crank torque was observed that was even more pronounced in the pull phase than in the push phase. Furthermore, participants showed an increase in shoulder internal rotation and abduction and a decrease in elbow flexion and retroversion. These changes were negatively correlated with performance. At high workloads, it seems that power output is more limited by the transition from pull to push phase than at low workloads. It is suggested that successful athletes demonstrate small alterations of their kinematic profile due to increasing workloads. Future studies should replicate and expand the test spectrum (sprint and continuous loads) as well as use methods like surface electromyography (sEMG) with elite handcyclists.
Digitalisierung bezeichnet die Nutzung großer Datenmengen, die zu einer umfassenden Vernetzung aller Bereiche der Wirtschaft und Gesellschaft führen wird (BMWi, 2015 und ähnlich Köhler/Wollschläger, 2014: 79). Sie umfasst die Erhebung von analogen Informationen („Big Data“ in einem engen Sinne; z.B. O´Leary, 2013), ihre Speicherung in einem digitaltechnischen System (lokale Speicherung oder „Cloud Computing“ durch die Weiterentwickelung des Internets; z.B. Hashem et al., 2015: 101), die Analyse und Interpretation sowie den Transfer in andere Systeme („Internet der Dinge“ bzw. „Internet of Things“; z.B. Ashton, 2009).