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Mathematical modeling of the neuro-musculoskeletal system in healthy subjects has been pursued extensively. In post-stroke patients, however, such models are very primitive. Besides improving our general understanding of how stroke affects the limb motions, they can be used to evaluate rehabilitation strategies by computer simulations before clinical evaluations. A planar neuro-musculoskeletal arm model for post-stroke patients is developed. The main idea is to use a set of new coefficients, Muscle Significance Factors (MSF), to incorporate the effects of stroke in the muscle control performance. The model uses the optimal control theory to mimic the performance of the CNS and a two-link... 

Computational models of the central nervous system after a stroke helps to reveal the physiological mechanisms that may have strong impacts on the neuro-motor rehabilitation approaches. This paper studies the stroke subject's motor control mechanism in reaching movements by extending the previous study by incorporating the kinematics of motion as well as neural disconnection between the muscles and the CNS to further develop a planar patient specific neuro-musculoskeletal model of arm. The developed model was calibrated to eight post-stroke individuals by altering the Muscle Significance Factors (MFS) using numerical optimization to match the simulated motions with those measured...