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  1. 1

    Horse gait analysis using wearable inertial sensors and machine learning

    Rana, M., Mittal, V.
    Published in Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology (2025)
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  2. 2

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

    Aram, S., Thompson, I. M., Hudson, D. A., Banks, J.
    Published in ISBS Proceedings Archive: Vol. 43: Iss. 1 (2025)
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  3. 3

    Expertise and coordination in show jumping: Investigating lumbar motion

    Régnault, N., Olivier, A., Bideau, N.
    Published in ISBS Proceedings Archive: Vol. 43: Iss. 1 (2025)
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  4. 4

    Evaluating the influence of sensor configuration and hyperparameter optimization on wearable-based knee moment estimation during running

    Höschler, L., Halmich, C., Schranz, C., Koelewijn, A. D., Schwameder, H.
    Published in International Journal of Computer Science in Sport (2025)
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  5. 5

    Comparison of an IMU- and magnet timing gate- based system and an opto-electronic device for analysing running biomechanics

    Neuhaus, N., Breuker, K., Schmidt, M.
    Published in Sports Engineering (2025)
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  6. 6

    Validation of step time and asymmetry detection algorithm in high-intensity running with Movesense IMU

    Martín Gómez, R., Kamstra, H., Allevard, E., Pollet-Villard, L., Cotter, J., Lamb, P.
    Published in Journal of Biomechanics (2025)
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  7. 7

    A novel method for assessing added mass in front crawl swimming

    Carmigniani, R., Coloretti, V., Brunel, T., Bosetto, P., Fantozzi, S., Cortesi, M., Zamparo, P.
    Published in Journal of Biomechanics (2025)
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  8. 8

    The influence of menstrual cycle in heart rate variability and performance - a case study of a highly-trained female long-distance runner

    Barría-Miranda, F., Azócar-Gallardo, J., Ñancupil-Andrade, L., Ñancupil-Andrade, A., Garcia-Carrillo, E., Campos-Uribe, V., Cresp-Barria, M.
    Published in Journal of Human Sport & Exercise (2025)
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  9. 9

    Sensor fusion of high-frequency RTK GNSS and IMU improves the detection performance of running characteristics of each step in 400 m run

    Keisuke, O., Kiyoshi, H., Naoto, M., Akiko, K., Wako, K., Hiroshi, N., Shunya, U., Masaki, T.
    Published in 29th Annual Congress of the European College of Sport Science, 2-5 July 2024, Book of Abstracts (2024)
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  10. 10

    Predicting running vertical ground reaction forces using neural network models based on an IMU sensor

    Li, S., Pan, J., Wang, D., Yuan, S., Yang, J., Hao, W.
    Published in Sensors (2025)
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  11. 11

    Agreement between an inertial measurement unit (IMU) algorithm and a photoelectric system for analysing spatiotemporal variables during overground and treadmill running

    Miqueleiz, U., Aguado-Jimenez, R., Lecumberri, P., Gorostiaga, E. M.
    Published in Sports Biomechanics (2025)
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  12. 12

    Technical stroke regulations discriminate pacing effectiveness during a 5-km indoor pool race

    Bouvet, A., Pla, R., Nicolas, G., Bideau, N.
    Published in International Journal of Sports Physiology and Performance (2025)
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  13. 13

    Prediction of vertical ground reaction forces under different running speeds: integration of wearable IMU with CNN-xLSTM

    Chen, T., Xu, D., Zhou, Z., Zhou, H., Shao, S., Gu, Y.
    Published in Sensors (2025)
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  14. 14

    Repeatability of vertical ground reaction force estimation during running on the athletics track on 3 different days

    Scheltinga, B. L., Buurke, J. H., Kok, J. N., Reenalda, J.
    Published in Journal of Applied Biomechanics (2025)
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  15. 15

    Estimating sagittal knee and ankle moment during running using only inertial measurement units: a top-down inverse dynamics approach

    van Middelaar, R. P., van Rijswijk, N. T., Wouda, F. J., Veltink, P. H., Reenalda, J.
    Published in Sports Biomechanics (2025)
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  16. 16

    Reliability of running gait variability measures calculated from inertial measurement units

    Jones, B. D. M., Wheat, J., Middleton, K., Carey, D. L., Heller, B.
    Published in Journal of Biomechanics (2025)
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  17. 17

    From lab to field: validity and reliability of inertial measurement unit-derived gait parameters during a standardised run

    Webber, E., Leduc, C., Emmonds, S., Eglon, M., Hanley, B., Iqbal, Z., Sheoran, S., Chaisson, C., Weaving, D.
    Published in Journal of Sports Sciences (2024)
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  18. 18

    Applying multi-purpose commercial inertial sensors for monitoring equine locomotion in equestrian training

    Fercher, C., Bartsch, J., Kluge, S., Schneider, F., Liedtke, A.M., Schleichardt, A., Ueberschär, O.
    Published in Sensors (2024)
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  19. 19

    Simulating effects of sensor-to-segment alignment errors on IMU-based estimates of lower limb joint angles during running

    Potter, M. V.
    Published in Sports Engineering (2025)
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  20. 20

    Comparing the maximal horizontal deceleration demands between a novel acceleration to deceleration assessment and the 505 change of direction test

    Philipp, N. M., Scott, A. A., Caldwell, B. R., Cabarkapa, D., Johnson, Q. R., Fry, A. C.
    Published in Journal of Human Sport & Exercise (2024)
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