Search Results - Carter, J.

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  1. 1

    Estimation of lower limb joint moments using consumer realistic wearable sensor locations and deep learning - finding the balance between accuracy and consumer viability

    Carter, J., Chen, X., Cazzola, D., Trewartha, G., Preatoni, E.
    Published in Sports Biomechanics (2025)
    “…Carter, J.…”
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  2. 2

    A support vector machine algorithm can successfully classify running ability when trained with wearable sensor data from anatomical locations typical of consumer technology

    Carter, J. A., Rivadulla, A. R., Preatoni, E.
    Published in Sports Biomechanics (2022)
    “…Carter, J. A.…”
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  3. 3

    Support vector machines can classify runner's ability using wearable sensor data from a variety of anatomical locations

    Carter, J. A., Rivadulla, A. R., Preatoni, E. “…Carter, J. A.…”
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  4. 4

    Dietary nitrate supplementation improves sprint and high-intensity intermittent running performance

    Thompson, C., Vanhatalo, A., Jell, H., Fulford, J., Carter, J., Nyman, L., Bailey, S. J., M.Jones, A. M.
    Published in Nitric Oxide (2016)
    “…Carter, J.…”
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  5. 5

    Does flexibility exercise affect running economy? A brief review

    Carter, J., Greenwood, M.
    Published in Strength and Conditioning Journal (2015)
    “…Carter, J.…”
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  6. 6

    Cardiopulmonary physiology and responses of ultramarathon athletes to prolonged exercise

    Blaber, A. P., Walsh, M. L., Carter, J. B., Seedhouse, E. L., Walker, V. E. “…Carter, J. B.…”
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