Abstract
The incorporation of virtual humans with realistic interaction properties in the design of products and services can play a very crucial role in terms of their accessibility and ergonomy. Digital Human Modeling (DHM) and simulation has gained importance in the past few years and allows designers easily observe and evaluate the interaction of the designed product with a virtual user having specific needs and/or preferences. Simulation can be used to study and compare alternative designs or to troubleshoot existing systems. It offers to designers the opportunity to explore how a new system might behave before the real prototype is developed, or how an existing system might perform if altered, thus reducing development time and costs. But even if many remarkable researches in this direction can be found in the literature, a holistic framework including a formal definition of virtual users with disabilities, a detailed description of user tasks taking into account alternative modalities and the use of assistive devices, in order to be used in different simulation frameworks, has not yet been proposed. The core concept of this PhD research is to empower the accessibility of ICT and non-ICT technologies by introducing an innovative user modelling technique for the elderly and disabled. This new user modelling methodology is able to describe in detail a large variety of possible disabilities, the affected by the disabilities tasks as well as the physical, cognitive and behavioural/psychological user characteristics. An extension of UsiXML1 language has been developed, in order to express the proposed Virtual User Models (VUMs) in a machine-readable format. Research has been conducted, in order to determine how the values of various disability parameters vary over individuals and whether these values follow any common probability distribution (e. g.: Gaussian, Poisson, etc.). The great importance of finding such a correlation lies on the fact that it enables making realistic assumptions for different percentages of the disabled population. For instance, if the mean value and the standard deviation of visual acuity for people with myopia is known and we also know that visual acuity follows the Gaussian probability distribution, we could find the value of visual acuity for the 80%, 90%, etc. of people with myopia. Tools for supporting and putting the proposed user modeling methodology into practice have been also developed.