To live independently with a high quality of life, older adults must maintain the ability to perform activities of daily living, including walking and climbing stairs. However, 25% of adults aged 55 and over have difficulty walking one-quarter of one mile and 20% have difficulty climbing 10 steps. These functional limitations may be associated with age-related changes in muscle strength, motor control, and joint mechanics. However, how these age-related neuromusculoskeletal changes affect the ability of muscles to facilitate movement has not been established. Moreover, the underlying mechanisms that determine how muscles contribute to movement, and how these interactions change with age, are not well understood.

Given the wide array of musculoskeletal models from which to choose to investigate muscle function during movement, we created dynamic simulations of gait using four models to determine the effects of model choice on simulated joint mechanics, muscle activations, and muscle forces. We found that differences in coordinate system definitions between models altered joint kinematics and kinetics while discrepancies in muscle parameters and joint moments altered muscle activations and forces. Our findings also revealed that additional model complexity yielded greater error between experimental and simulated measures, suggesting less complex models are sufficient model for studying walking in healthy young adults.

We developed a new method for determining the potential of individual muscles to contribute to movement using a simple 4-link 2D model that does not require data from extensive experimental and simulation techniques. The new method can evaluate the effects of kinematic and strength modifications on improving a patient’s ability to perform a task significantly faster than traditional methods. We verified our method’s predictions of a muscle’s ability to contribute to movement against that estimated by traditional simulation techniques. This methodology supplies the framework for the design of new technology to enhance a clinician’s ability to determine how modifications to kinematics and muscle strength could improve a patient’s ability to perform a task.

We generated dynamic simulations of gait in healthy older and young adults to determine if muscle contributions to gait differed between age groups. We found older adults generated greater gluteus maximus contributions and smaller iliopsoas contributions, compared to those of young adults. Though there were no age-group differences in distal muscle contributions, altered ankle kinematics may be associated with differences in ankle moments between age-groups. Our findings suggest the combined effects of muscular and kinematic alterations may lead to differences in gait between healthy older and young adults.

Finally, we applied non-negative matrix factorization to experimental and simulated muscle activation patterns of young and older adults walking at their self-selected speed to determine if modular control of gait differs between age groups. We found modular organization derived from experimental activation patterns is similar between healthy older and young adults. However, experimental and simulated muscle activations do not reduce to the same set of modules.

This dissertation advances the field towards a more broadly accessible understanding of the relationship between joint kinematics, motor control, and muscle function, the effects of aging on this relationship, and how changes to this relationship affect the ability of muscles to contribute to movement. By deconstructing the complex interactions of the skeletal, muscular, and nervous systems, these studies establish a framework for future research to identify neuromuscular and biomechanical sources of impaired movement to ultimately inform the development of clinical interventions that preserve physical function, mobility, and quality of life in older adults and individuals with movement disorders.