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This paper examines the influence of adaptations of motion-intensive virtual reality training based on multiple physiological measurement data on training efficiency. We present a concept adapting difficulty and visual aspects of virtual reality training by deriving mental workload from selected physiological measurement data. We implemented a respective proof of concept and conducted a user study ( \(n = 20\) ) to validate the concept. Results show a general positive trend as well as significantly shorter training time, less number of errors and perceived effort.

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Increasing Training Efficiency of Motion-Intensive Virtual Reality Training with Adaptations Based on Physiological Measurement Data

  • 会议论文

  • 发表日期：

    2025年

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  • Fabio Genz,
  • Dieter Kranzlmüller

摘要

This paper examines the influence of adaptations of motion-intensive virtual reality training based on multiple physiological measurement data on training efficiency. We present a concept adapting difficulty and visual aspects of virtual reality training by deriving mental workload from selected physiological measurement data. We implemented a respective proof of concept and conducted a user study ( \(n = 20\) ) to validate the concept. Results show a general positive trend as well as significantly shorter training time, less number of errors and perceived effort.