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WPI (Worcester Polytechnic Institute)

Computer Science Department
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CyPRESS Exergame Enjoyment

Joshua Audibert, Elijah Gonzalez, Ryan Orlando, and Nicholas Wong

Advisors: Mark Claypool and Emmanuel Agu

Major Qualifying Project MQP-EOQ-0032
Computer Science, WPI
Terms ABC 2016-2017

Abstract

Only one in three children are physically active each day due to the growing online lifestyle and the lack of enjoyable alternatives besides organized sports. One viable alternative is mobile exercise games (exergames). Currently, there are many problems with the process of connecting people to exergames they would enjoy, including that it can be difficult to discover new enjoyable exergames and an exergame recommender system does not exist. To help create this system, we determined that it is possible to measure enjoyment in exergames using accelerometer and gyroscope data from their smartphone. By running experiments using the Just Dance Now and Pokemon Go mobile exergames, we were able to create a final classification model that was able to correctly predict enjoyment 75% of the time.


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