The vestibular apparatus allows to perform audiological and equilibrium human functions and to capture movements with respect to gravity. Damages to the vestibular system causes diseases that can be measured by using Vestibular Evoked Myogenic Potentials (VEMPs) test. The test produces a lot of data that has to be collected and analyzed to allow a disease study and classification. We propose a framework that includes algorithms able to perform pathology distribution and classification. It has been tested on electronic patient records loaded from the University Hospital database. The software allows to manage the structure and framework and a blind application of one of the available classification techniques shows a relation among gender and vestibular apparatus disease.
['Domenico Mirarchi', 'Claudio Petrolo', 'Giovanni Canino', 'Patrizia Vizza', 'Salvatore Cuomo', 'Giuseppe Chiarella', 'Pierangelo Veltri']
Applying Mining Techniques to Analyze Vestibular Data