Implicit context representation Cartesian genetic programming for the assessment of visuo-spatial ability

Authors:
Stephen L. Smith;Michael A. Lones
Affiliations:
Intelligent Systems Research Group, Department of Electronics, University of York, Heslington, York, UK;Intelligent Systems Research Group, Department of Electronics, University of York, Heslington, York, UK
Venue:
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Year:
2009

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Abstract

In this paper, a revised form of Implicit Context Representation Cartesian Genetic Programming is used in the development of a diagnostic tool for the assessment of patients with neurological dysfunction such as Alzheimer's disease. Specifically, visuo-spatial ability is assessed by analysing subjects' digitised responses to a simple figure copying task using a conventional test environment. The algorithm was trained to distinguish between classes of visuo-spatial ability based on responses to the figure copying test by 7-11 year old children in which visuo-spatial ability is at varying stages of maturity. Results from receiver operating characteristic (ROC) analysis are presented for the training and subsequent testing of the algorithm and demonstrate this technique has the potential to form the basis of an objective assessment of visuo-spatial ability.