1999
DOI: 10.1016/s0021-9290(98)00158-4
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Bone position estimation from skin marker co-ordinates using global optimisation with joint constraints

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Cited by 794 publications
(536 citation statements)
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References 16 publications
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“…Anthropometric characteristics were obtained. Following the method of Cappozzo et al [8], 36 reflective markers (14 mm diameter), including 30 lower extremity markers, were placed on the participant [18,19]. An additional six markers were placed on the steps to later identify their spatial locations.…”
Section: Methodsmentioning
confidence: 99%
“…Anthropometric characteristics were obtained. Following the method of Cappozzo et al [8], 36 reflective markers (14 mm diameter), including 30 lower extremity markers, were placed on the participant [18,19]. An additional six markers were placed on the steps to later identify their spatial locations.…”
Section: Methodsmentioning
confidence: 99%
“…L M o : L T s was maintained). Virtual markers were placed on the model to match the locations of the experimental markers and an inverse kinematics algorithm was used to determine the joint angles of the model over 10 complete gait cycles [41,42]. Ten right-side gait cycles were segmented using the measured ground reaction force to identify heel strike.…”
Section: Methodsmentioning
confidence: 99%
“…The model anthropomorphic properties as well as the muscle-tendon unit insertion, origin and their bone wrapping points were linearly scaled on the basis of the relative distances between experimental and corresponding virtual markers 44 . Inverse kinematics was solved for three-dimensional joint angles that minimized the least-squared error between experimental and virtual marker locations during dynamic trials 46 . The generated kinematics were then used to obtain dynamically consistent joint moments via residual reduction analysis, i.e.…”
Section: Model-based Estimationmentioning
confidence: 99%