Architecture for neurological coordination tests implementation

Abstract

This paper proposes a generic architecture for devising interactive neurological assessment tests, aimed at being implemented on a touchscreen device. The objective is both to provide a set of software primitives that allow the modular implementation of tests, and to contribute to the standardization of test protocols. Although our original goal was the application of machine learning methods to the analysis of test data, it turned out that the construction of such framework was a pre-requisite to collect enough data with the required levels of accuracy and reproducibility. In the proposed architecture, tests are defined by a set of stimuli, responses, feedback information, and execution control procedures. The presented definition has allowed for the implementation of a particular test, the Finger-Nose-Finger, that will allow the exploitation of data with intelligent techniques.