Modeling and Motor Learning of Reaching Movements in Virtual Environments

The paper presents an analysis of human reaching movements in manipulation of flexible objects. To predict the trajectory of human hand we resort to two models, the lowest polynomial order model for the hand movement and the minimum hand jerk model. First, we derive analytical solutions for these models for the dynamic environment represented by a multi-mass linear flexible object. Then, we present initial experimental results. It is shown that the lowest polynomial order model does not fit with the experimental data while the prediction by the minimum hand jerk criterion matches the experimental patterns with reasonable accuracy.