An evaluation of motor models of handwriting

A general method is presented for describing and analyzing biomedical handwriting models. Using Laplace's transform theory, a model can be represented in what is called the neural firing-rate domain. Consistent terminology is proposed to facilitate model evaluation and comparison. An overview of previously published models suggests that they could be described using this method, with second- and third-order linear model representation. Fourteen simplified theoretical models are simulated in an experiment designed to study the parameter domain in which handwriting is controlled by the nervous system in order to gain insight into which type of model provides the best reconstruction of natural handwriting. Results show that velocity-controlled models produce the best outputs, with no significant difference between second- and third-order systems. In handwriting, fine motor behavior is thus velocity-controlled. These findings agree with other recent automatic signature verification results and are of interest for a number of applications, from pattern recognition to handwriting education. >