Development a planar neuro-musculoskeletal arm model in post-stroke patients

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 experimentally. Eventually, the reaches generated by our model replicated the features observed in reaches by individual stroke survivors with a promising level of accuracy. Our results show that trajectory planning after stroke still argues for optimal control of movement in which internal models can play a significant role.