Abstract
The analysis of human movement using 4D data is explored in this paper. Using the CAESAR database, reference distributions of body segment volumes and 3D mesh vertices connected to anatomical landmarks were created. A child (10 years old, male) with lower limb asymmetry of idiopathic origin was investigated, comparing the asymmetries seen in “A-pose” and level gait to the reference data. Pelvic tilt curves were calculated from pelvic anatomical markers using either a single vertex or a collection of vertices. The trajectories of pelvic markers, as in conventional marker-based motion analysis, and the distributions of vertices obtained from the CAESAR database, were used for that purpose. The two distributions of pelvic tilt curves were very similar to each other, with mean values differing less than 1º, and standard deviations around 3º in both cases. When the anatomical landmarks were defined as single points, pelvic tilt remained within one standard deviation of the probabilistic distributions of tilt curves but biased towards greater values (2º greater than the means of those distributions) This preliminary study shows the capability of using 4D scanning technology for assessing volumetric asymmetries, opening new frontiers in biomechanics in pathologies that have asymmetric pathological features (e.g. lymphedema).
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Acknowledgements
This research has been developed in the framework of the IBERUS project: Technological Network of Biomedical Engineering applied to degenerative pathologies of the neuromusculoskeletal system in clinical and outpatient settings (CER-20211003), CERVERA Network financed by the Ministry of Science and Innovation through the Center for Industrial Technological Development (CDTI), and charged to the General State Budgets 2021 and the Recovery, Transformation and Resilience Plan.
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De Rosario, H., Scataglini, S., Basso, F., Alemany, S., Saeys, W., Truijen, S. (2023). Applications of Using 4D Scanning Technologies in Biomechanics. In: Scataglini, S., Harih, G., Saeys, W., Truijen, S. (eds) Advances in Digital Human Modeling . DHM 2023. Lecture Notes in Networks and Systems, vol 744. Springer, Cham. https://doi.org/10.1007/978-3-031-37848-5_11
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