ESTG - Mestrado em Ciência de Dados
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Percorrer ESTG - Mestrado em Ciência de Dados por autor "António, João Miguel Abrantes Marques"
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- Modelling gamified exercise data to support therapeutic monitoring of fraily in older adultsPublication . António, João Miguel Abrantes Marques; Malheiro, Ricardo Manuel da SilvaResearch indicates that video games can provide mental stimulation and stress relief, which may contribute to the well-being of gamers. With the continued growth of the video game industry and its demographic, attempts to evoke similar feelings of enjoyment in non-game environments have been proposed, gradually defining the concept of ’gamification’. Over the last two decades, gamification has shown positive effects on user engagement and participation in tasks across several fields of research, such as education and workplace productivity. In the area of healthcare, specifically in subjects of physical therapy and rehabilitation exercise, the implementation of game design choices and social features is evident in mobile applications and smart devices, however, despite the outlined benefits, the adoption of these strategies by the elderly population faces methodological difficulties that bar its progress. Research highlights a lack of process standardization, the employment of inefficient game concepts, and improper design choices for the referred demographic. In this thesis, the complications associated with the employment of gamification strategies in senior healthcare are explored and discussed, leading up to the proposal of a methodological approach to improving the success of such strategies, through the conception and development of a data mining project applied to a real clinical scenario. The use of this approach has been shown to effectively improve the quality of gamification and aid in making better business decisions based on the underlying data. Moreover, five distinct data models and processes were developed, acting on improving the platform with feedback collection, automated game suggestions and logical patient profiling based on physical factors.