The convex wrapping algorithm: A method for identifying muscle paths using the underlying bone mesh |
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| Authors: | Eric Desailly Philippe Sardain Nejib Khouri Daniel Yepremian Patrick Lacouture |
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| Affiliation: | 1. Fondation Ellen Poidatz, 77310 St. Fargeau-Ponthierry, France;2. UPR 3346 CNRS – Université de Poitiers – ENSMA, Département Génie Mécanique et Systèmes Complexes, Axe RoBioSS “Robotique Biomécanique Sport Santé”, SP2MI, BP 30179, 86962 Futuroscope Cedex, France;3. Hopital Armand Trousseau, AP-HP, 75571 Paris Cedex 12, France;1. LISSI, University of Paris-Est-Créteil, France;2. Univ Lyon, Université Claude Bernard Lyon 1, IFSTTAR, UMR_T9406, LBMC, F69622 Lyon, France;3. Department of Movement, Human and Health Sciences, Università degli Studi di Roma “Foro Italico”, Rome, Italy;4. Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, Università degli Studi di Roma “Foro Italico”, Rome, Italy;5. Department of Mechanical Systems Engineering, Tokyo University of Agriculture and Technology, Japan;1. Department of Biomedical Engineering University of California Davis, United States;2. Department of Biomedical Engineering, Department of Mechanical Engineering, Department of Orthopaedic Surgery, University of California Davis, United States;1. Human Performance Laboratory, Faculty of Kinesiology, University of Calgary, Calgary, AB, Canada T2N 1N4;2. Department of Kinesiology, University of Maryland, College Park, MD 20745, USA;3. Department of Kinesiology, Iowa State University, Ames, IA 50011, USA;2. Department of Bioengineering and Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112, USA;3. Department of Orthopedics, University of Utah, Salt Lake City, UT 84108, USA;4. Department of Physical Therapy, University of Utah, Salt Lake City, UT 84108, USA |
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| Abstract: | Associating musculoskeletal models to motion analysis data enables the determination of the muscular lengths, lengthening rates and moment arms of the muscles during the studied movement. Therefore, those models must be anatomically personalized and able to identify realistic muscular paths. Different kinds of algorithms exist to achieve this last issue, such as the wired models and the finite elements ones. After having studied the advantages and drawbacks of each one, we present the convex wrapping algorithm. Its purpose is to identify the shortest path from the origin to the insertion of a muscle wrapping over the underlying skeleton mesh while respecting possible non-sliding constraints. After the presentation of the algorithm, the results obtained are compared to a classically used wrapping surface algorithm (obstacle set method) by measuring the length and moment arm of the semitendinosus muscle during an asymptomatic gait. The convex wrapping algorithm gives an efficient and realistic way of identifying the muscular paths with respect to the underlying bones mesh without the need to define simplified geometric forms. It also enables the identification of the centroid path of the muscles if their thickness evolution function is known. All this presents a particular interest when studying populations presenting noticeable bone deformations, such as those observed in cerebral palsy or rheumatic pathologies. |
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