| Sumario: | Subject-specific computer simulation studies have been used to describe the function of individual muscles in healthy and post-stroke gait, and the results of musculoskeletal simulations can be useful for understanding an individual's response to rehabilitation. Subject-specific information about muscle force and volitional activation can help to improve the predictive power of computer generated musculoskeletal models, but require accurate and reliable measurement techniques to obtain. The goals of this dissertation are to enhance our ability to create subject-specific models of individuals post-stroke and improve our understanding of muscle coordination in individuals post-stroke.As part of this dissertation, we identified available compensatory strategies for muscle weakness during gait by simulating activation deficits in multiple muscle groups. Subject-specific simulations were created to determine the changes in modeled activation and function of the ankle plantar flexor muscles in patients post-stroke after a targeted function electrical stimulation intervention. A new adjustment equation was developed and used to assess the ability of muscle volume obtained through magnetic resonance imaging (MRI) to estimate the maximum force generating ability (MFGA) of the plantar flexor muscle group for individuals post-stroke. Lastly, we created musculoskeletal simulations of individuals post-stroke with subject-specific muscle force and activation data.We found that musculoskeletal models were unable to recreate normal gait patterns with simultaneous impairment of the plantar flexor, dorsiflexor, and hamstrings muscle groups. Simulations of individuals post-stroke showed a new pattern of model-predicted activation for the plantar flexor muscles after training, suggesting that the subjects activated these muscles with more appropriate timing following the intervention. Muscle volume obtained via MRI was found to overestimate the force generating ability of the paretic limb plantar flexors. Finally, the inclusion of subject-specific muscle data resulted in greater model-predicted force and activation levels for the hip and knee flexors, which agree with previously reported compensation patterns.By identifying how muscles can interact, clinicians may be able to develop specific strategies to best address an individual's needs. The results of this dissertation suggest that subject-specific isometric force and activation data may affect the accuracy of model predictions and should be used when building musculoskeletal models of individuals post-stroke.
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