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  1. 1

    Validity and reliability of an on-bike sensor system for the determination of aerodynamic drag in cycling

    Hopker, J. G., Barnes, C., Fennell, C. R. J., Gibson, S.
    Published in European Journal of Sport Science (2025)
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  2. 2

    Validity and Reliability of an on-bike sensor system for the determination of aerodynamic drag in cycling

    Hopker, J., Barnes, C., Fennell, C., Gibson, S.
    Published in SportRxiv Preprints (2024)
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  3. 3

    Assessing ambient temperature measurements in road cycling races

    Pinedo-Jauregi, A., Romarate, A.
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  4. 4

    Validity of current smartwatches for triathlon training: How accurate are heart rate, distance, and swimming readings?

    Jacko, T., Bartsch, J., von Diecken, C., Ueberschär, O.
    Published in Sensors (2024)
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  5. 5

    Artificial intelligence in cycling - Live positional tracking using on-bike aerodynamic sensors

    Barnes, C., Hopker, J., Gibson, S.
    Published in Journal of Science and Cycling (2024)
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  6. 6

    Validity of a commercial wearable sensor measuring respiratory frequency in cycling

    Greco, G., Innocenti, L., Massaroni, C., Nicolò, A.
    Published in Journal of Science and Cycling (2024)
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  7. 7

    Estimation of LT with dynamic transfer function models with commercial HR and power sensor data

    Stessens, L., Gouwy, R., Gielen, J., Aerts, J.-M.
    Published in Journal of Science and Cycling (2024)
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  8. 8

    Multi-sensor based analysis of the changeovers in team pursuit

    Decorte, R., Verstockt, S., Slembrouck, M.
    Published in Journal of Science and Cycling (2024)
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  9. 9

    Using inertial measurement units to examine selected joint kinematics in a road cycling sprint: a series of single cases

    Morbey, S., Tronslien, M., Kong, K., Chapman, D. W., Netto, K.
    Published in Sensors (2024)
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  10. 10

    Will wearable sweat lactate sensors be the next big thing in cycling?

    Van Hoovels, K., Boone, J., Cuartero, M., Crespo, G. A.
    Published in Journal of Science and Cycling (2023)
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  11. 11

    Optimizing performance in cycling through machine learning

    Boone, J., Latré, S., Verdonck, T.
    Published in Journal of Science and Cycling (2023)
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  12. 12

    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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  13. 13

    Low cost and personalized highlight generation during cycling races

    Decorte, R., De Bock, J., Slembrouck, M., Verstockt, S.
    Published in Journal of Science and Cycling (2023)
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  14. 14

    Concurrent validity and reliability of two portable powermeters (Power2Max vs. PowerTap) to measure different types of efforts in cycling

    Iglesias-Pino, J., Herrero-Molleda, A., Saavedra-García, M. Á., García-López, J.
    Published in Sensors (2023)
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  15. 15

    Measuring muscle oxygenation in endurance sports with wearable nirs - from validation to application

    Yogev, A
    Published 2023
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  16. 16

    Cycling modelling under uncontrolled outdoor conditions using a wearable sensor and different meteorological measurement methods

    Millour, G., Plourde-Couture, F., Domingue, F.
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  17. 17

    The effects of simulated duathlon on multisegment running external and internal load in well-trained triathletes

    Rojas-Valverde, D., Oliva-Lozano, J. M., Gutierrez-Vargas, R., Pino-Ortega, J., Muyor, J. M., Gomez-Carmona, Gómez-Carmona, C. D.
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  18. 18

    Measurement of simple reaction time of the cyclist in the laboratory and natural environment condition

    Zak, M., Mikrut, G., Sobota, G.
    Published in Sensors (2023)
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  19. 19

    The validity of ultra-short-term heart rate variability during cycling exercise

    Tanoue, Y., Nakashima, S., Komatsu, T., Kosugi, M., Kawakami, S., Kawakami, S., Michishita, R., Higaki, Y., Uehara, Y.
    Published in Sensors (2023)
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  20. 20

    Wie man mit einer IMU und neuronalen Netzen die Trittfrequenz im Radsport messen kann (How to measure the pedaling frequence in cycling with an IMU and neural networks)

    Hollaus, B., Volmer, J., Fleischmann, T.
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