Modeling Kinematic Features of Human Handwriting using Model Predictive Control

Handwriting is one of the high practiced and complex movements of human. Most of the proposed models belong to bottom-up models, and therefore they could not reflect how the human´s handwriting produces. In this paper we are going to describe some aspects of human´s handwriting that we could rarely see in the other models. Our model is based on the neurological and physiological research. In this proposed model, we want to prove that humans use internal models to predict their movements in their writing. According to the wide range of research, it seems that human´s handwriting is based on predictive control. Therefore we are going to suggest a handwriting model using model predictive control (MPC). Our results show that the model could provide handwritings like humans kinematic features. As our results show it has a high robustness and its accuracy is more than 84%.