Preventing dyspraxia: a project for the creation of a computational diagnostic system based on the theory of embodied cognition

Abstract

Dyspraxia is a disorder of internal representation and programming of voluntary movement that can compromise the development of higher cognitive functions and personality. It is therefore important to have diagnostic tools that allow us to diagnose early motor dysfunctions that are the basis of the disorder in order to be able to quickly intervene avoiding the stabilization of deficient processes. In this paper we intend to propose a computational diagnostic model based on the theory of embodied cognition. The main cognitive function integrated by multimodal neuronal clusters is the integration of space and time, which occurs through precise articulations of the experience of being in the world. The work presents the development in three phases of a computational diagnostic system. The development of the method starts from the identification of motor sequences aimed at detecting the deficits of the praxic functions; in a subsequent phase it evolves into the creation of a neural network aimed at recognizing these diagnostic motor sequences; finally it ends with the production of prototypes of movement that can be used by the system as a standard for the identification of deficits of voluntary movement in children. The future perspective is that of a systematic use of this computational diagnostic system in the classes of the kindergarten.