Many young adults do not exercise enough, choosing instead to spend time on electronic media (smartphone, Internet). Exergames, which gamify physical activity, can be effective at increasing physical activity in an enjoyable way. However, exergame discovery is still manual, ad hoc and challenging. Our objective is to research and develop Cypress, a cyber-physical recommender system that 1) uses smart-phone sensing to actively monitor user enjoyment of exergames played 2) learns the types of games liked and 3) recommends similar games when users become bored, thus keeping users engaged and exercising.

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