Design and implementation of interactive mobile application for autistic children in physical education class

Abstract

Each autistic child has different characteristics and severity of symptoms ranging from not being able to do daily routine tasks such as exercising by themselves to not being able to care for themselves and needing caretakers to look after them for most of the time. In the Autistic Research Centre, Khon Kaen University Demonstration School, Thailand, every morning, one of their routine tasks is exercise, especially on the treadmill, which can reduce their weight and improve their focus on school during the day. The aim of this research is to find video interaction in the form that encourage autistic children's exercise on a treadmill suitable for individual child. Six interaction techniques were designed and tested. The techniques included: Face Detection (FD), Upper Body Detection (UBD), Color Detection (CD), QR Code Detection (QCD), Motion Detection (MD), and Adaptive Video Interaction (AVI). All interactions were developed on the iOS platform and tested on eight autistic children. Each child was tested at least 12 sessions on the treadmill, and performance of the six techniques were evaluated from the accuracy of application detecting the child's presence on the treadmill compared to the actual number of times that each child disappeared. The results showed that the AVI was the most suitable technique for autistic children with an average accuracy rate of 92.31%. The study shows that the application is able to reduce the caretaker's burden and motivate autistic children to focus while exercising.