Effect of various upper limb multibody models on soft tissue artefact correction: A case study |
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Affiliation: | 1. CIC INSERM 1432, Plateforme d''Investigation Technologique, CHU Dijon, France;2. Univ Lyon, Université Claude Bernard Lyon 1, IFSTTAR, LBMC UMR_T9406, F69622 Lyon, France;3. CNRFR – Rehazenter, Laboratoire d’Analyse du Mouvement et de la Posture, 1 rue André Vésale, L-2674 Luxembourg, Luxembourg;4. Laboratoire de simulation et de modélisation du mouvement, Département de kinésiologie, Université de Montréal, 1700, rue Jacques Tétreault, Laval, QC H7N 0B6, Canada;5. Research Center, Sainte-Justine Hospital, 3175 Côte-Ste-Catherine, Montreal, Quebec H3T 1C5, Canada;1. Univ Lyon, Université Claude Bernard Lyon 1, IFSTTAR, LBMC UMR_T9406, F69622 Lyon, France;2. CEA, LIST, Interactive Simulation Laboratory, Gif-sur-Yvette F-91191, France;1. University of Paris-Est Créteil, Laboratory of Image, Signal and Intelligent Systems, LISSI, France;2. Univ Lyon, Université Claude Bernard Lyon 1, IFSTTAR, UMR_T9406, LBMC, F69622 Lyon, France;3. Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, Università degli Studi di Roma “Foro Italico”, Italia;4. Department of Movement, Human, and Health Sciences, Università degli Studi di Roma “Foro Italico”, Italia;5. Department of Electrical and Computer Engineering, University of Waterloo, Canada;6. Department of Mechanical Systems Engineering, Tokyo University of Agriculture and Technology, Japan;7. LIRMM UMR 5506 CNRS, Montpellier University, France;8. NaturalPad, Montpellier, France;1. Instituto de Biomecánica de Valencia, Universitat Politècnica de València, Valencia, Spain;2. CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Spain;3. Centro de Investigación en Ingeniería Mecánica, Universitat Politècnica de València, Valencia, Spain;1. Université de Lyon, F-69622, Lyon, IFSTTAR, LBMC, UMR_T9406, Université Lyon 1, France;2. Covidien, Trévoux, 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 |
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Abstract: | Soft tissue artefacts (STA) introduce errors in joint kinematics when using cutaneous markers, especially on the scapula. Both segmental optimisation and multibody kinematics optimisation (MKO) algorithms have been developed to improve kinematics estimates. MKO based on a chain model with joint constraints avoids apparent joint dislocation but is sensitive to the biofidelity of chosen joint constraints. Since no recommendation exists for the scapula, our objective was to determine the best models to accurately estimate its kinematics. One participant was equipped with skin markers and with an intracortical pin screwed in the scapula. Segmental optimisation and MKO for 24-chain models (including four variations of the scapulothoracic joint) were compared against the pin-derived kinematics using root mean square error (RMSE) on Cardan angles. Segmental optimisation led to an accurate scapula kinematics (1.1° ≤ RMSE ≤ 3.3°) even for high arm elevation angles. When MKO was applied, no clinically significant difference was found between the different scapulothoracic models (0.9° ≤ RMSE ≤ 4.1°) except when a free scapulothoracic joint was modelled (1.9° ≤ RMSE ≤ 9.6°). To conclude, using MKO as a STA correction method was not more accurate than segmental optimisation for estimating scapula kinematics. |
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Keywords: | Soft tissue artefact Multibody kinematics optimisation Upper limb Shoulder Kinematics model |
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