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  1. 1

    Aerobars position effect: What is the interaction between aerodynamic drag and power production?

    Térol, S., Costes, A., Malmert, A., Soto-Romero, G., Brunet, E.
    Published in Journal of Science and Cycling (2024)
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  2. 2

    INSCYD physiological performance software is valid to determine the maximal lactate steady state in male and female cyclists

    Poffé, C., Van Dael, K., Van Schuylenbergh, R.
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  3. 3

    A fuzzy-based software tool used to predict 110m hurdles results during the annual training cycle

    Przednowek, K., Wiktorowicz, K., Krzeszowski, T., Iskra, J.
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  4. 4

    Reliability and sensitivity of the notio device and aer-oscale service to quantify cyclists' drag coefficients in outdoor conditions

    Bruez, A., Caillou, Q., Dugenne, T., Peron, T., Perrey, S., Lambolais, T.
    Published in Journal of Science and Cycling (2023)
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  5. 5

    Towards an operational framework for designing training based sports virtual reality performance simulators

    Shepherd, J., Carter, L., Pepping, G.-J., Potter, L.-E.
    Published in Proceedings (2018)
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  6. 6

    Utility of inscyd athletic performance software to determine maximal lactate steady state and maximal oxygen uptake in cyclists

    Podlogar, T., Cirnski, S., Bokal, Š., Kogoj, T.
    Published in Journal of Science and Cycling (2022)
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  7. 7

    Is additive manufacturing improving performance in Sports? A systematic review

    Novak, J. I., Novak, A. R.
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  8. 8

    The use of a smartphone application in monitoring HRV during an altitude training camp in professional female cyclists: A preliminary study

    Javaloyes, A., Mateo-March, M., Manresa-Rocamora, A., Sanz-Quinto, S., Moya-Ramón, M.
    Published in Sensors (2021)
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  9. 9

    Design and implementation of a novel component oriented system for performance monitoring of elite athletes

    Chakravorti, N.
    Published 2017
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  10. 10

    The use of online training tools in competition cyclists during COVID19 confinement in Spain

    Moreno, A., Zarceño, E. M. L., Serrano, M. A.
    Published in Frontiers in Physiology (2021)
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  11. 11

    The show must go on - virtualisation of sport events during the COVID-19 pandemic

    Westmattelmann, D., Grotenhermen, J.-G., Sprenger, M., Schewe, G.
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  12. 12

    New approach for planning the mountain bike training with virtual coach

    Rauter, S.
    Published in Trends in Sport Sciences (2018)
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  13. 13

    A mathematical model for simulating cycling: applied to track cycling

    Fitton, B., Symons, D.
    Published in Sports Engineering (2018)
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  14. 14

    Practical pedaling skill items extraction for efficient pedaling training with surface EMG wear

    Saisho, O., Nakayama, M., Tanaka, K., Yokozek, D.
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  15. 15

    Towards machine learning on data from professional cyclists

    Hilmkil, A., Ivarsson, O., Johansson, M., Kuylenstierna, D., van Erp, T.
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  16. 16

    Analysis of a bicyclist`s head injury in lateral and frontal impact using the human full-body model

    Teng, T.-L., Liang, C.-C., Nguyen, V.-H.
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  17. 17

    Case study on use of cloud computing, IoT, big data, machine learning, DevOps in Tour de France

    Sagar Nangare
    Published 2017
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  18. 18

    Agreement between Powertap, Quarq and Stages power meters for cross-country mountain biking

    Miller, M. C., Macdermid, P. W., Fink, P. W., Stannard, S. R.
    Published in Sports Technology (2015)
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  19. 19

    The proceedings of the 13th Australasian Conference on Mathematics and Computers in Sport

    R. Stefani, A. Schembri
    Published 2016
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  20. 20

    Using deception to establish a reproducible improvement in 4-km cycling time trial performance

    Shei, R.-J., Thompson, K., Chapman, R., Raglin, J., Mickleborough, T.
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