Musculoskeletal model-based inverse dynamic analysis under ambulatory conditions using inertial motion capture
| Autor: | Mark de Zee, H. Martin Schepers, Giovanni Bellusci, Peter H. Veltink, Angelos Karatsidis, Moonki Jung, Michael Skipper Andersen |
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| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Adult
Male Movement 0206 medical engineering Biophysics Biomedical Engineering Walking 02 engineering and technology Models Biological Motion capture 09 Engineering Inverse dynamics 03 medical and health sciences 0302 clinical medicine Gait (human) medicine Humans Ground reaction force Mechanical Phenomena Mathematics Ligaments 02 Physical Sciences Muscles Mathematical analysis Inertial motion capture 11 Medical And Health Sciences 22/4 OA procedure 020601 biomedical engineering Healthy Volunteers Sagittal plane Biomechanical Phenomena Moment (mathematics) Kinetics Transverse plane medicine.anatomical_structure Gait analysis Musculoskeletal modeling Joints 030217 neurology & neurosurgery Ground reaction forces and moments |
| Zdroj: | Karatsidis, A, Jung, M, Schepers, M, Bellusci, G, de Zee, M, Veltink, P H & Andersen, M S 2019, ' Musculoskeletal model-based inverse dynamic analysis under ambulatory conditions using inertial motion capture ', Medical Engineering & Physics, vol. 65, pp. 68-77 . https://doi.org/10.1016/j.medengphy.2018.12.021 Medical Engineering and Physics, 65(March), 68-77. Elsevier |
| ISSN: | 1350-4533 |
| Popis: | Inverse dynamic analysis using musculoskeletal modeling is a powerful tool, which is utilized in a range of applications to estimate forces in ligaments, muscles, and joints, non-invasively. To date, the conventional input used in this analysis is derived from optical motion capture (OMC) and force plate (FP) systems, which restrict the application of musculoskeletal models to gait laboratories. To address this problem, we propose the use of inertial motion capture to perform musculoskeletal model-based inverse dynamics by utilizing a universally applicable ground reaction force and moment (GRF&M) prediction method. Validation against a conventional laboratory-based method showed excellent Pearson correlations for sagittal plane joint angles of ankle, knee, and hip ( ρ = 0.95 , 0.99, and 0.99, respectively) and root-mean-squared-differences (RMSD) of 4.1 ± 1.3°, 4.4 ± 2.0°, and 5.7 ± 2.1°, respectively. The GRF&M predicted using IMC input were found to have excellent correlations for three components (vertical: ρ = 0.97 , RMSD = 9.3 ± 3.0 %BW, anteroposterior: ρ = 0.91 , RMSD = 5.5 ± 1.2 %BW, sagittal: ρ = 0.91 , RMSD = 1.6 ± 0.6 %BW*BH), and strong correlations for mediolateral ( ρ = 0.80 , RMSD = 2.1 ± 0.6 %BW) and transverse ( ρ = 0.82 , RMSD = 0.2 ± 0.1 %BW*BH). The proposed IMC-based method removes the complexity and space restrictions of OMC and FP systems and could enable applications of musculoskeletal models in either monitoring patients during their daily lives or in wider clinical practice. |
| Databáze: | OpenAIRE |
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