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Marco J. Konings, Jordan Parkinson, Inge Zijdewind and Florentina J. Hettinga

to athletes in competitive sports. 5 Indeed, the presence of a virtual opponent has been shown to improve cycling performance, 6 – 8 and the pacing behavior of the virtual opponent has been shown to affect the initial pace of cyclists in laboratory-controlled conditions. 7 The performance

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Alba Reguant-Closa, Margaret M. Harris, Tim G. Lohman and Nanna L. Meyer

and macronutrients to body mass (BM), weight categories were defined by gender (60 kg females [f] and 75 kg males [m]). Each sport dietitian created 18 plates. To avoid food waste, half of the plates were created “virtually” on paper, whereas the other half were created with food. For the virtual

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Gunnar Treff, Kay Winkert, Katja Machus and Jürgen M. Steinacker

based on the criteria that would normally cause TERM auto , when activated. The virtual test duration at TERM auto was compared with the actual test duration after TERM exhaust . Metabolic Analysis Gas exchange and ventilation were measured with a Metamax 3x (Cortex Biophysics, Leipzig, Germany) to

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Bart Roelands and Kevin De Pauw

. Artificial intelligence experts have been working on the implementation of virtual-, augmented-, and mixed-reality sessions into the microcycle planning of athletes. These strategies seemed science fiction only a few years ago but are now being used in tactical training sessions. The integration of

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Michael J. Davies, Bradley Clark, Laura A. Garvican-Lewis, Marijke Welvaert, Christopher J. Gore and Kevin G. Thompson

, appears the most effective form of deception to elicit performance improvements. 5 In performance deception trials, athletes have raced against a virtual on-screen pacer whom they believed was programmed to mimic mean power output (MPO) from their previous best performance. In reality, the pacer was

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Luca Filipas, Emiliano Nerli Ballati, Matteo Bonato, Antonio La Torre and Maria Francesca Piacentini

the other athletes. Renfree et al 31 have highlighted how the behavior of an athlete can influence the pacing strategy of all the others. Specifically, Konings et al 32 reported how pacing behavior is altered depending on the pacing profile of a virtual opponent. In this case, in fact, the decision

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Marco J. Konings and Florentina J. Hettinga

of pacing behavior. 2 , 4 As shown before in observational and experimental studies, an opponent could be such an affordance, inviting exercisers to adjust their pacing behavior. 4 – 6 For example, the presence of a virtual opponent has been revealed to improve performance. 5 , 7 – 9 Moreover

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Bettina Karsten, Jonathan Baker, Fernando Naclerio, Andreas Klose, Antonino Bianco and Alfred Nimmerichter

pedal force at the start of each TT. To replicate real-world TT cycling, participants consequently used a self-pacing strategy where gearing was adjusted throughout efforts using the virtual gear changer mounted to the handlebars. Feedback over elapsed time and strong encouragement were provided

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Gerda Strutzenberger, Adam Brazil, Timothy Exell, Hans von Lieres und Wilkau, John D. Davies, Steffen Willwacher, Johannes Funken, Ralf Müller, Kai Heinrich, Hermann Schwameder, Wolfgang Potthast and Gareth Irwin

, a virtual toe marker was created half-way between the 2 RSP markers. Step length and width were identified using the toe markers. Step frequency of the first step was calculated as 1/(first stance contact time + flight time) and step velocity as the product of step frequency and step length. Kinetic

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Mostafa Zarei, Hamed Abbasi, Abdolhamid Daneshjoo, Mehdi Gheitasi, Kamran Johari, Oliver Faude, Nikki Rommers and Roland Rössler

N , Yusof A . The effects of comprehensive warm-up programs on proprioception, static and dynamic balance on male soccer players . PLoS ONE . 2012 ; 7 ( 12 ): e51568 . PubMed ID: 23251579 doi:10.1371/journal.pone.0051568 12. Donath L , Rössler R , Faude O . Effects of virtual reality