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Using MediaPipe Machine Learning to Design Casual Exertion Games to Interrupt Prolonged Sedentary Lifestyle

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HCI in Games (HCII 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14046))

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Abstract

Casual exergames have shown potential in providing sufficient levels of exertion to decrease sedentary behavior. However, previous casual exergame implementations do not follow the guidelines of allowing for shorter (2–3 min) active breaks during more regular increments. To evaluate if casual exergames could be applied following the guidelines of shorter more regular increments we designed and developed a casual exergame using MediaPipe. The resulting game, Balloon Pump, was evaluated at a game and cosplay festival with 60 participants playing the game. After game play, perceived exertion, control and immersion, and overall experience of the game, was measured and the performance and number of movements were noted. The results from the evaluation study showed that the game was perceived as controllable, had produced sufficient levels of exertion, and was perceived as fun. The immersive experience of the game was low and the participants commented on several ways in which this aspect could be improved, such as adding more incentives and variation in the game.

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Author information

Authors and Affiliations

  1. Department of Computer and Information Science, Linköping University, Linköping, Sweden

    Erik Berglund, Izabella Jedel & Aseel Berglund

Authors
  1. Erik Berglund
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  2. Izabella Jedel
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  3. Aseel Berglund
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Editors and Affiliations

  1. DePaul University, Chicago, IL, USA

    Xiaowen Fang

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© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Berglund, E., Jedel, I., Berglund, A. (2023). Using MediaPipe Machine Learning to Design Casual Exertion Games to Interrupt Prolonged Sedentary Lifestyle. In: Fang, X. (eds) HCI in Games. HCII 2023. Lecture Notes in Computer Science, vol 14046. Springer, Cham. https://doi.org/10.1007/978-3-031-35930-9_16

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  • DOI: https://doi.org/10.1007/978-3-031-35930-9_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-35929-3

  • Online ISBN: 978-3-031-35930-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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