Modeling of Musculoskeletal System Using Biomechanics and Knowledge Engineering Approaches: Clinical Benefits and Limitations

Understanding of mechanical behaviors of the human body is a challenge to take appropriate medical decisions (e.g. patient's diagnosis or treatment). To achieve this objective, two modeling approaches were studied and confronted in order to highlight the benefits and limitations of each approach to clinical problems. The biomechanical model is including anatomical geometries, anthropometrical data, mechanical properties and motion analysis data. A new type of model named meta-model is based on knowledge engineering representation, data mining and artificial intelligence methods. Orthopedic pediatric pathologies (Polio, clubfoot, cerebral palsy) were studied to evaluate the accuracy and robustness of these modeling approaches. Methodological confrontation through clinical benefits and limitations of each modeling approach and their complementarities were analyzed and presented. To conclude, even if input data and modeling of each approach are different, these two approaches are closely complementary for better understanding of musculoskeletal disorders leading to best diagnosis and treatment prescriptions.