Search Results

Refine Results
  1. 1

    Using unsupervised machine learning to characterize recovery patterns in elite canoe-kayak athletes across the Olympic training year

    Foucaud, A., Durand, F., Meric, H.
    Save to List
    Saved in:
    Access source
  2. 2

    A machine learning approach for saddle height classification in cycling

    Bing, F., Zhang, G., Wei, L., Zhang, M.
    Save to List
    Saved in:
    Access source
  3. 3

    Reliability of the durability concept in professional cyclists: a field-based study

    Mateo-March, M., Barranco-Gil, D., Hernández-Belmonte, A., Javaloyes, A., Muriel, X., Pallarés, J. G., Lucia, A., Valenzuela, P. L.
    Save to List
    Saved in:
    Access source
  4. 4

    The influence of the environment on the calculation of drag area in cycling: Contrasting results between indoor and outdoor field tests

    Ordiñana-Pérez, M., Zabala, M., Blasco-Lafarga, C.
    Save to List
    Saved in:
    Access source
  5. 5

    Enhancing endurance performance predictions: the role of movement velocity in metabolic simulations demonstrated by cycling cadence

    Dunst, A. K., Hesse, C., Ueberschär, O.
    Save to List
    Saved in:
    Access source
  6. 6

    Machine learning prediction of pulmonary oxygen uptake from muscle oxygen in cycling

    Li, N., Hu, W., Ma, Y., Xiang, H.
    Published in Journal of Sports Sciences (2024)
    Save to List
    Saved in:
    Access source
  7. 7

    Thrifty reservoir: A phenomenological concept model for cycling

    Pieri, G.
    Published in Journal of Science and Cycling (2024)
    Save to List
    Saved in:
    Access source
  8. 8

    Incorporating the maximal mean power profile in time trial simulations for more efficient optimal pacing strategy calculations

    Zignoli, A., Biral, F.
    Published in Journal of Science and Cycling (2024)
    Save to List
    Saved in:
    Access source
  9. 9

    Physical performance estimation in practice: A systematic review of advancements in performance prediction and modeling in cycling

    Stessens, L., Gielen, J., Meeusen, R., Aerts, J.-M.
    Save to List
    Saved in:
    Access source
  10. 10

    Reliability of recovery heart rate variability measurements as part of the Lamberts Submaximal Cycle Test and the relationship with training status in trained to elite cyclists

    Lamberts, R. P., van Erp, T., Javaloyes, A., Eken, M. M., Langerak, N. G., Tam, N.
    Save to List
    Saved in:
    Access source
  11. 11

    Modelling of a cyclist`s power for time trials on a velodrome

    Bos, L., Slawinski, M. A., Slawinski, R. A., Stanoev, T.
    Published in Sports Engineering (2024)
    Save to List
    Saved in:
    Access source
  12. 12

    Ein neuartiger Ansatz zur Bestimmung der zeit- und ermüdungsabhängigen Effizienz bei maximalen Radsprints (A novel approach to determine time- and fatigue-dependent efficiency in maximal cycling sprints)

    Dunst, A. K., Hesse, C., Ueberschär, O.
    Published in dvs-Biomechanik 2023 Tagungsband (2023)
    Save to List
    Saved in:
  13. 13

    Estimation of anaerobic threshold with dynamic transfer function models based on heart rate and power in cycling

    Stessens, L., Jean-Marie, A.
    Published in Journal of Science and Cycling (2023)
    Save to List
    Saved in:
    Access source
  14. 14

    On technical considerations of velodrome track design

    Stanoev, T.
    Published in Sports Engineering (2023)
    Save to List
    Saved in:
    Access source
  15. 15

    Anaerobic work capacity in cycling: the effect of computational method

    Andersson, E. P., Bachl, P., Schmuttermair, A., Staunton, C. A., Stöggl, T. L.
    Save to List
    Saved in:
    Access source
  16. 16

    Modelling road cycling as motion on a curve

    Nee, P. J., Herterich, J. G.
    Published in Sports Engineering (2022)
    Save to List
    Saved in:
    Access source
  17. 17

    Insights in road cycling downhill performance using aerial drone footages and an `optimal` reference trajectory

    Zignoli, A., Fruet, D.
    Published in Sports Engineering (2022)
    Save to List
    Saved in:
    Access source
  18. 18

    Imputation of non-participated race results

    Janssens, B., Bogaert, M.
    Save to List
    Saved in:
    Access source
  19. 19

    Sensor-based performance monitoring in track cycling

    Steyaert, M., De Bock, J., Verstockt, S.
    Save to List
    Saved in:
    Access source
  20. 20

    An intelligent curve warning system for road cycling races

    Zignoli, A.
    Published in Sports Engineering (2021)
    Save to List
    Saved in:
    Access source

Search Tools: