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This work presents the evaluation of two interaction techniques in games using a smartwatch as a control device: On-screen Continuous Gesture Recognition and air gestures with HMM. The experiment involved participants, aged between 17 and 50 years old. The results indicated a clear preference for the On-screen Continuous Gesture Recognition technique, highlighting its effectiveness and acceptance by users. The analysis of the System Usability Scale (SUS) results showed a positive evaluation for this technique, while the HMM technique was considered less favorable for endless running games. Participants showed a preference for the on-screen touch approach, emphasizing its intuitiveness and satisfactory interaction experience. The findings suggest that On-screen Continuous Gesture Recognition provides a smoother and more natural interaction compared to air gestures with HMM.

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Exploring Gesture-Based Interaction in Smartwatch Games: A Comparative Study Between Continuous Gesture Recognition and Hidden Markov Models

  • 会议论文

  • 发表日期：

    2025年

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  • Leonardo Silva,
  • Deborah Fernandes,
  • Emília Nogueira,
  • Juliana Félix,
  • Luciana Cardoso,
  • Renan Aranha,
  • Thamer Horbylon Nascimento,
  • Fabrizzio Soares

摘要

This work presents the evaluation of two interaction techniques in games using a smartwatch as a control device: On-screen Continuous Gesture Recognition and air gestures with HMM. The experiment involved participants, aged between 17 and 50 years old. The results indicated a clear preference for the On-screen Continuous Gesture Recognition technique, highlighting its effectiveness and acceptance by users. The analysis of the System Usability Scale (SUS) results showed a positive evaluation for this technique, while the HMM technique was considered less favorable for endless running games. Participants showed a preference for the on-screen touch approach, emphasizing its intuitiveness and satisfactory interaction experience. The findings suggest that On-screen Continuous Gesture Recognition provides a smoother and more natural interaction compared to air gestures with HMM.