Validation of a Virtual Arm Model for Movement Control and Rehabilitation

The purpose of this study is to validate a computational model that can be applied to studies of movement control and rehabilitation. A two joint, six muscle, virtual arm (VA) model has been developed in previous work [Song et al. 2008a]. The VA model driven by internal noise of neural control of muscles, i.e. the signal dependent noise (SDN), displays a behavior of kinematic variability that is often observed in human motor performance. In the present study, simulations were carried out to generate variability behaviors of the VA model under open-loop conditions. The hand stiffness was evaluated through a theoretical calculation method. Simulation results were compared to the corresponding behaviors observed in human subjects. It was shown that the shape, magnitude, and orientation of the simulated hand stiffness and variability were consistent with those of experimental measurements cross a range of posture conditions. This general agreement proves that the computational model could be a viable approach to replicating the realistic human motor behaviors. The model could be a useful tool for simulation of motor deficits caused by centrally impaired functions, like Parkinson´s disease and stroke, as well as for the development of rehabilitation strategies for these neurological disorders.