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  1. 1

    A machine learning approach for saddle height classification in cycling

    Bing, F., Zhang, G., Wei, L., Zhang, M.
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  2. 2

    Changes in stroke performance in 13-14 year old swimmers over an annual training cycle

    Malinovsky, M. S., Arishin, A. V., Pogrebnoy, A. I.
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  3. 3

    Breath-by-breath measurement of respiratory frequency and tidal volume with a multiple-camera motion capture system during cycling incremental exercise

    Massaroni, C., Nicolò, A., Lopes, A.L.d.C., Romano, C., Pinnelli, M., Sarro, K., Schena, E., Cerveri, P., Sacchetti, M., Silvestri, S., Silvatti, A. P.
    Published in Sensors (2025)
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  4. 4

    Mean stability and between-session reliability of cycling biomechanics variables in elite pursuit cyclists

    Williams, D., Dunn, M., Worsfold, P., Newton, D., Faulkner, S. H., d`Andrea, F., Wheat, J.
    Published in Sports Biomechanics (2025)
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  5. 5

    Capabilities of «motion capture» systems in identifying features of cyclists pedaling techniques

    Sushchenko, V. P., Lukashevich, D. A., Guseynov, D. I.
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  6. 6

    Validation of LEOMO inertial measurement unit sensors with marker-based three-dimensional motion capture during maximum sprinting in track cyclists

    Thompson, R., Bini, R. R., Paton, C., Hébert-Losier, K.
    Published in Journal of Sports Sciences (2024)
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  7. 7

    Longitudinal bending stiffness of cycling footwear - What is stiff enough?

    Litzenberger, S., Tran, D.-M., Michel, F. I.
    Published in Journal of Science and Cycling (2023)
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  8. 8

    Automated PTZ framing of track cyclists using timing loops

    Slembrouck, M., Decorte, R., De Bock, J., Verstockt, S.
    Published in Journal of Science and Cycling (2023)
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  9. 9

    A literature overview of modern biomechanical-based technologies for bike-fitting professionals and coaches

    Millour, G., Torres Velásquez, A., Domingue, F.
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  10. 10

    Kinematic analysis of bicycle pedalling using 2D- and 3D-motion capture systems

    Garcia-Lopez, J., Abal del Blanco, P.
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  11. 11

    The validity and intra-tester reliability of markerless motion capture to analyse kinematics of the BMX Supercross gate start

    Grigg, J., Haakonssen, E., Rathbone, E., Orr, R., Keogh, J. W. L.
    Published in Sports Biomechanics (2018)
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  12. 12

    Estimating the projected frontal surface area of cyclists from images using a variational framework and statistical shape and appearance models

    Drory, A., Li, H., Hartley, R.
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  13. 13

    Optoelectronic analysis of cyclists` position before and after a bike fit: A case study of a professional women`s cycling team

    Fronczek-Wojciechowska, M., Kopacz, K., Kosielski, P., Padula, G.
    Published in Trends in Sport Sciences (2016)
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  14. 14

    Kinetic properties and EMG activity of normal and over-speed pedaling in track sprint cyclists: A case study

    Liao, H. T., Lin, Y. C., Pandy, M., Tang, W. T.
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  15. 15

    Intelligente Bewegungsbetreuung - Einsatzgebiet von Ubiquitous-Computing-Technologien mit hohem Potential

    Baca, A.
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  16. 16

    Forward seat position effects on cycling kinematics

    Hanaki-Martin, S., Mullinaeux, D., Jeon, K., Shapiro, R.
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  17. 17

    Statistics of bicycle rider motion

    Moore, J. K., Hubbard, M., Schwab, A. L., Kooijman, J. D. G., Peterson, D. L.
    Published in Procedia Engineering (2010)
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  18. 18

    Markerless motion capture of man-machine interaction

    Rosenhahn, B., Schmaltz, C., Brox, T., Weickert, J., Cremers, D., Seidel, H. P.
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