Musculoskeletal disorders cover a broad range of health problems related to the locomotion apparatus (i.e. muscles, bones, cartilages, ligaments, tendons, joints, vascular system and nerves). Accurate diagnosis and appropriate treatment of musculoskeletal disabilities needs a deeper understanding of anatomical evolution and functional behaviors of biological tissues (e.g. muscle, tendon, bone) and their interactions at different length (e.g. molecule, cell, organ, system, full-body, population) and time scales. Experimental research showed its ultimate usefulness to provide informative data (e.g. physiological, morphological, mechanical, biochemical properties) to improve the understanding of the etiology and evolution of musculoskeletal disorders. Besides, in silico musculoskeletal modeling has been intensively developed and used to provide non-invasively immeasurable data inside the biological tissue such as muscle force or tissue stress/train behavior. Thus, the use of both experimental and in silico researches aims to provide evident facts and knowledge for a deeper understanding of the human body functions leading to optimize the diagnosis and treatment of musculoskeletal disorders. One of the main difficulties is to provide reliable experimental data reflecting the multi-physical behavior of the systems of interest. These experimental data are commonly used as input data of numerical models to quantify output responses through physical and/or biological laws expressed by constitutive mathematical equations. Moreover, these data may be used to validate the simulation outcomes. However, uncertainties on the experimental data exist from several factors such as human variability and differences in protocols parameters and techniques. Thus, the true values of these data could never be measured or estimated. These uncertainties are extremely important and need to be accounted to provide reliable simulation results, especially in the framework of in silico medicine.
In this Research Topic, the following subjects are welcomed:
- Single-scale or multi-scale musculoskeletal modeling
- Advanced parameter sensitivity study
- Parameter uncertainty quantification and propagation
- Model uncertainty and propagation
- Systematic model verification and validation
Musculoskeletal disorders cover a broad range of health problems related to the locomotion apparatus (i.e. muscles, bones, cartilages, ligaments, tendons, joints, vascular system and nerves). Accurate diagnosis and appropriate treatment of musculoskeletal disabilities needs a deeper understanding of anatomical evolution and functional behaviors of biological tissues (e.g. muscle, tendon, bone) and their interactions at different length (e.g. molecule, cell, organ, system, full-body, population) and time scales. Experimental research showed its ultimate usefulness to provide informative data (e.g. physiological, morphological, mechanical, biochemical properties) to improve the understanding of the etiology and evolution of musculoskeletal disorders. Besides, in silico musculoskeletal modeling has been intensively developed and used to provide non-invasively immeasurable data inside the biological tissue such as muscle force or tissue stress/train behavior. Thus, the use of both experimental and in silico researches aims to provide evident facts and knowledge for a deeper understanding of the human body functions leading to optimize the diagnosis and treatment of musculoskeletal disorders. One of the main difficulties is to provide reliable experimental data reflecting the multi-physical behavior of the systems of interest. These experimental data are commonly used as input data of numerical models to quantify output responses through physical and/or biological laws expressed by constitutive mathematical equations. Moreover, these data may be used to validate the simulation outcomes. However, uncertainties on the experimental data exist from several factors such as human variability and differences in protocols parameters and techniques. Thus, the true values of these data could never be measured or estimated. These uncertainties are extremely important and need to be accounted to provide reliable simulation results, especially in the framework of in silico medicine.
In this Research Topic, the following subjects are welcomed:
- Single-scale or multi-scale musculoskeletal modeling
- Advanced parameter sensitivity study
- Parameter uncertainty quantification and propagation
- Model uncertainty and propagation
- Systematic model verification and validation