Developing technological solutions to assist children with ASD with application to real-life and diagnostic scenarios

The thesis aims at presenting the development of technological solutions aimed at assisting in two different aspects (one diagnostic-oriented and one oriented to real-life problems) in the life of children with autistic spectrum disorders. The development is framed into a process of “adaptive prototyping”, which is here refined to meet the specific needs of software development arising in the considered application domain. The first application domain is motivated by the fact that children with autism perceive sensory experiences differently and have problems accepting unknown social contexts. A notable case is that of dental care setting, where there are many strong sound-visual stimuli, which are usually not found in known environments such as home, school or therapy session rooms. This usually upsets a child with autism, often forcing dentists to administer an anesthetic even to perform normal dental hygiene. In recent years, technology-enhanced systems and apps have been developed to help people with autism adapt to new contexts and cope with distressing social situations. In the thesis we discuss the development of a web application (MyDentist) which provides dentists, parents and children with a set of resources to teach children with autism the proper oral procedures at home and correct behavior during dental visits. MyDentist includes multimodal games and activities to lighten children’s tension and to make them familiar with dental procedures. Games and activities can be personalized according to child’s needs and preferences. A unique software environment allows professionals to take and collect photos and videos during dental visits and make them accessible to parents and caregivers in the private profile of each child. In the second applicative domain, we considered the use of Internet of Things devices to monitor the behavior of children with autism in a niche application, namely the observation of the children during their games, which is a common test performed by specialists to diagnose autistic spectrum disorders in an early stage. Specifically, the thesis describes the development of an IoT system that employs miniaturized sensors and data fusion algorithms based on machine learning to identify automatically the movements applied to the toys by the children. Starting from this two cases we propose a methodological solution to face many of the typical challenges that several e-health scenarios involving ASD needs could pose to the software designer.