Non-linear Analyses of Cell proliferation in the central nervous system reveal stochastic and deterministic components

Abstract

Stroke is one of the leading causes for long-term disability in the United States. Robot-aided rehabilitation has facilitated the functional recovery of chronic stroke victims. In this study, two models were developed to aid the design of a rehabilitation robot driven by pneumatic muscle (PM) actuators, which will be applied in the treatment of the upper-limb sensorimotor deficits of stroke patients. A biomechanical model of the musculoskeletal system with exoskeleton robot powered by PM was implemented to examine the initial parameters of PM based on the kinematics and dynamics of PM assisted arm-reaching and self-feeding tasks. The outputs of the model provided guidelines for the optimal design of robot's structure. Additionally, the model can determine the necessary auxiliary force and the activation timing pattern of each PM during multi-joint coordinated movement for the robot's dynamic control. Inverse-dynamics biomechanical model generates the joint torques required to perform the movement. In addition to the musculoskeletal model, we propose a simple method to estimate the self-generated net muscle torques, therefore, to provide quantitative assessment of motor improvement of stroke patients during the therapy.