Analytical study of the effects of soft tissue artefacts on functional techniques to define axes of rotation |
| |
Affiliation: | 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. Department of Kinesiology, KU Leuven, Belgium;2. Department of Rehabilitation Sciences, KU Leuven, Belgium;1. Department of Kinesiology, Université de Montréal, Montreal, QC, Canada H3C 3J7;2. CIC INSERM 1432, Plateforme d’Investigation Technologique, CHU Dijon, France;3. Univ Lyon, Université Lyon 1, IFSTTAR, LBMC UMR_T9406, F69622, Lyon, France;4. Karolinska Institutet, Stockholm, Sweden;1. Université de Lyon, F-69622, Lyon; IFSTTAR, LBMC, UMR_T9406, Bron; Université Lyon 1, Villeurbanne, France;2. Department of Movement, Human and Health Sciences, Università degli Studi di Roma “Foro Italico”, Rome, Italy;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. 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. Laboratory of Movement Analysis and Measurement, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland;2. Laboratoire de recherche en imagerie et orthopédie, Centre de recherche du Centre Universitaire Hospitalier de Montréal, École de technologie supérieure, Montréal, Canada;3. Univ Lyon, Université Claude Bernard Lyon 1, IFSTTAR, LBMC UMR_T9406, F69622 Lyon, France;4. Interuniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, Università degli Studi di Roma “Foro Italico”, Rome, Italy |
| |
Abstract: | The accurate location of the main axes of rotation (AoR) is a crucial step in many applications of human movement analysis. There are different formal methods to determine the direction and position of the AoR, whose performance varies across studies, depending on the pose and the source of errors. Most methods are based on minimizing squared differences between observed and modelled marker positions or rigid motion parameters, implicitly assuming independent and uncorrelated errors, but the largest error usually results from soft tissue artefacts (STA), which do not have such statistical properties and are not effectively cancelled out by such methods. However, with adequate methods it is possible to assume that STA only account for a small fraction of the observed motion and to obtain explicit formulas through differential analysis that relate STA components to the resulting errors in AoR parameters. In this paper such formulas are derived for three different functional calibration techniques (Geometric Fitting, mean Finite Helical Axis, and SARA), to explain why each technique behaves differently from the others, and to propose strategies to compensate for those errors. These techniques were tested with published data from a sit-to-stand activity, where the true axis was defined using bi-planar fluoroscopy. All the methods were able to estimate the direction of the AoR with an error of less than 5°, whereas there were errors in the location of the axis of 30–40 mm. Such location errors could be reduced to less than 17 mm by the methods based on equations that use rigid motion parameters (mean Finite Helical Axis, SARA) when the translation component was calculated using the three markers nearest to the axis. |
| |
Keywords: | Functional calibration Axis of rotation Soft tissue artefacts Geometric fitting Finite helical axis Knee joint |
本文献已被 ScienceDirect 等数据库收录! |
|