Playing Games via Personalized Gestural Interaction - Ascari, Rúbia E. O. Schultz; Silva, Luciano; Pereira, Roberto (Anais Estendidos do Simpósio Brasileiro de Jogos e Entretenimento Digital (SBGames), 2021)
Motivation is a key element in the learning process, and using games for this goal is an undeniably attractive option. However, individuals with motor disabilities are still finding themselves excluded from many game-based school approaches. This paper presents a solution developed for people with motor and speech impairments that includes a game-based approach to contribute in this context. Based on a methodology in which gestures and their meanings are created and configured by users and their caregivers, we developed a Computer Vision system named PGCA that employs machine learning techniques to create personalized gestural interaction as an Assistive Technology resource for communication purposes. This personalized gestural interaction enabled disabled people to interact with the PGCA system and play a game using their remaining functional movements. Results from experiments carried out with the target audience indicate that the structure used in the developed system can be expanded to create new games, with different purposes, including to educational context.