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Radiation-training system with a custom survey-meter mock-up in a browser-based mixed reality environment

  • Hiroyuki Arakawa (Department of Health Sciences, Faculty of Medical Sciences, Kyushu University) ;
  • Toshioh Fujibuchi (Department of Health Sciences, Faculty of Medical Sciences, Kyushu University) ;
  • Kosuke Kaneko (Robert T.Huang Entrepreneurship Center, Kyushu University) ;
  • Yoshihiro Okada (Innovation Center for Educational Resources of Kyushu University Library, Kyushu University) ;
  • Toshiko Tomisawa (Department of Nursing Science, Hirosaki University Graduate School of Health Sciences)
  • Received : 2023.07.26
  • Accepted : 2024.01.31
  • Published : 2024.06.25

Abstract

Training for radiation protection and control requires a visual understanding of radiation, which cannot be perceived by the human senses. Trainees must also master the effective use of measuring instruments. Traditionally, such training has exposed trainees to radiation sources. Here, we present a novel e-training strategy that enables safe, exposure-free handling of a radiation measuring tool called a survey meter. Our mixed reality radiation-training system merges the physical world with a digital one. Collaborating with a mixed reality headset (HoloLens 2), this system constructs a mock-up of a survey meter in real-world space. The HoloLens 2 employs a browser-based application to visualize radiation and to simulate/share the use of the survey meter, including its physical movements. To provide a dynamic learning experience, the system adjusts the survey-meter mock-up readings according to the operator's movements, distance from the radiation source, the response time of survey meter, and shielding levels. Through this approach, we expect that trainees will acquire practical skills in interpreting survey-meter readings and gain a visual understanding of radiation in real-world situations.

Keywords

Acknowledgement

This work has been supported by the grant-in-aid for Scientific Research of JSPS KAKENHI (Grant Numbers JP21K07703) and by the Industrial Disease Clinical Research Grants (220201-01), Japan.

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