Chava musculoskeletal model

Musculoskeletal diseases, such as osteoarthritis and tendinopathy, impose a substantial burden on individuals and health care systems. As a community of scientists and clinicians, we have been largely ineffective in managing musculoskeletal diseases, as current prevalence, incidence, and socioeconomic burden are at alarming levels and projected to increase sharply in the coming decades. In particular, we have a limited understanding of how physical behavior, i.e., whole-body mechanics, influences tissue state, and this could intensity our failure to cure these prevalent and harmful diseases. It is known targeted strengthening and/or repair would be possible if an individual’s physical behavior could be altered to generate optimal mechanical signaling to musculoskeletal issues. In this research, we developed a new bioinspired multiscale forward finite element musculoskeletal model, which includes muscle, bone, ligaments, and soft-tissue, in Abaqus and concurrent with Isight and CATIA to deterministically investigate the individualized biofeedback of relevant mechanical signals to guide the clinical decision making, and design of implants and rehabilitation. The proposal will provide a new approach to link motor neuron behavior, physical behavior, and tissue mechanobiology, which can promote the understanding of human behaviors.