2023
DOI: 10.21203/rs.3.rs-2774614/v1
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Validity of neural networks in determining lower limb kinematics in stationary cycling

Abstract: Purpose: Increasing access to marker-less technology has enabled practitioners to obtain kinematic data more quickly. However, the validation of many of these methods is lacking. Therefore, the validity of pre-trained neural networks was explored in this study compared to reflective marker tracking from sagittal plane cycling motion. Methods: Twenty-six cyclists were assessed during stationary cycling at self-selected cadence and moderate intensity exercise. Standard video from their sagittal plane was obtaine… Show more

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