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 Pokémon Go mobile exergames, we were able to create a final classification model that was able to correctly predict enjoyment 75% of the time.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Orlando, Ryan Neil
• Wong, Nicholas Sze-Yu
• Audibert, Joshua D
• Gonzalez, Elijah Lee

Publisher

• Worcester Polytechnic Institute

Identifier

• E-project-032317-120730

Advisor

• Agu, Emmanuel O.
• Claypool, Mark L.

Year

• 2017

Date created

• 2017-03-23

Resource type

• Major Qualifying Project

Major

• Computer Science

Rights statement

• In Copyright