Kinematic Analysis of Patients with Charcot–Marie–Tooth Disease Using OpenSim
This study proposes a methodology for conducting computational simulations of pathological gait. The literature shows a consensus that biomechanical models for gait analysis should be formulated as control problems. To achieve this, it is common practice to guide the solution using kinematic or kinetic data to prevent temporal instability. The aim of this study is to implement a biomechanical model of the Charcot–Marie–Tooth disease in OpenSim software that enables more comprehensive simulations, which may in future involve the musculoskeletal system of patient and predictive studies. In this way, it will be possible to design specific active assistive devices tailored to each patient. Experimental gait data from six Charcot–Marie–Tooth patients were used. The dataset comprises three-dimensional trajectories of reflective markers placed according to the Davis-Heel protocol. The acquired data allowed a patient-specific adjustment of the biomechanical model. The inverse kinematic was solved, and the results were validated by comparing them with those obtained using the commercial BTS Bioengineering® software. The results show a strong alignment in ankle kinematics between the OpenSim model and the data generated by BTS Bioengineering®. Additionally, the kinematic results have been compared with normative curves, allowing the identification of potential areas for intervention using active assistive devices aimed at improving movement patterns of patients.
Authors
- Joaquín Ojeda (ORCID: https://orcid.org/0000-0002-6894-197X)
- M.J. Zarco-Periñán
- Ezequiel Martín-Sosa (ORCID: https://orcid.org/0000-0002-7484-3364)
- Patricia Ferrand-Ferri
- J. Mayo (ORCID: https://orcid.org/0000-0001-8752-8585)
- Francisco Romero (ORCID: https://orcid.org/0000-0001-6235-4435)
Institutions
- Hospital Universitario Virgen del Rocío (ES)
- Universidad de Huelva (ES)
- Universidad de Sevilla (ES)
- Universidad de Extremadura (ES)
Publication Details
- Journal
- Applied Sciences
- Published
- 2025-09-16
- DOI
- https://doi.org/10.3390/app151810104
- Primary Topic
- Hereditary Neurological Disorders
- Type
- article
- Field-Weighted Citation Impact
- 0.00