Exercise Intensity-Driven Level Design.

Area of Science:

• Human-Computer Interaction
• Game Design
• Sports Science

Background:

• Virtual reality (VR) and augmented reality (AR) games necessitate player movement.
• Designing engaging VR/AR levels requires balancing physical exertion to avoid player fatigue or insufficient challenge.
• Current level design methods often overlook the player's physical experience.

Purpose of the Study:

• To present a novel approach for optimizing game level designs in motion-based games.
• To systematically consider and control the physical challenge imposed on players.
• To enhance the design process for virtual and augmented reality experiences.

Main Methods:

• Representing game levels as assemblies of chunks, each with a defined exercise intensity.
• Formulating game level synthesis as an optimization problem to achieve desired intensity levels.
• Employing a Reversible-jump Markov chain Monte Carlo technique for trans-dimensional optimization to create variable-length levels.

Main Results:

• Demonstrated the approach's applicability in generating game levels for motion-based virtual reality games.
• Successfully synthesized game levels by assembling chunks based on player intensity.
• The method allows for the creation of levels with tailored physical demands.

Conclusions:

• The proposed optimization approach effectively addresses the challenge of designing physical exertion in VR/AR games.
• User evaluation confirmed the approach's ability to generate levels with desired physical challenge.
• This method offers a valuable tool for game designers creating immersive and physically balanced motion-based experiences.