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  1. 1

    Investigation of supervised machine learning for IMU-based swimming activity recognition

    Aram, S., Thompson, I. M., Hudson, D. A., Banks, J.
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  2. 2

    Beyond training: A personalized holistic injury prediction in triathletes

    Rossi, L., Rodrigues, B.
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  3. 3

    Accuracy of smartwatches in predicting distance running performance

    Dai, J., Chen, G., Gu, Z., Qi, Y., Xu, K.
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  4. 4

    Validity and reliability of movesense hr+ ecg measurements for high-intensity running and cycling

    Martín Gómez, R., Allevard, E., Kamstra, H., Cotter, J., Lamb, P.
    Published in Sensors (2024)
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  5. 5

    A single trunk-mounted wearable sensor to measure motor performance in triathletes during competition

    Chesher, S. M., Rosalie, S. M., Chapman, D. W., Charlton, P. C., van Rens, F. E. C. A., Netto, K. J.
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  6. 6

    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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  7. 7

    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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  8. 8

    Validation of Body Rocket on-bike wind-tunnel technology: Drag measurement accuracy and aerodynamic gains sensitivity

    DeGolier, E., Cibinel, A., Barnes, C.
    Published in Journal of Science and Cycling (2024)
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  9. 9

    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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  10. 10

    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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  11. 11

    Increasing step rate reduces peak and cumulative insole force in collegiate runners

    Madden, T. S., Hawkins, D. A.
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  12. 12

    The night-time sleep and autonomic activity of male and female professional road cyclists competing in the Tour de France and Tour de France Femmes

    Sargent, C., Jasinski, S., Capodilupo, E. R., Powers, J., Miller, D. J., Roach, G. D.
    Published in Sports Medicine - Open (2024)
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  13. 13

    Optimizing wearable device and testing parameters to monitor running-stride long-range correlations for fatigue management in field settings

    Fuller, J. T., Thewlis, D., Wills, J. A., Buckley, J. D., Arnold, J. B., Doyle, E., Doyle, T. L. A., Bellenger, C. R.
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  14. 14

    Wearable pressure sensors for swimming thrust analysis: a validation study

    Coloretti, V., Russo, G., Fantozzi, S., Cortesi, M.
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  15. 15

    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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  16. 16

    Wearable technology metrics are associated with energy deficiency and psychological stress in elite swimmers

    Lundstrom, E. A., De Souza, M. J., Koltun, K. J., Strock, N. C. A., Canil, H. N., Williams, N. I.
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  17. 17

    Haptic feedback system for swimming

    Hribernik, M., Umek, A., Dopsaj, M., Kos, A.
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  18. 18

    Accuracy of the tritonwear unit in high performance swimmers

    Campbell, A., McKenna, M., Sheath, M., Scott, B., Lobb, C.
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  19. 19

    Symmetry of propulsion exerted during tethered- and free-swimming

    Fantozzi, S., Fantozzi, S., Russo, G., Coloretti, V., Cortesi, M.
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  20. 20

    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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