Proceedings of the Workshop on Computation: Theory and Practice (WCTP 2025)

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Development of a BLS Self-Training Support System using MR and Sensor Devices

Authors
Shunsuke Goto1, Yoko Tsukamoto2, Hiroshi Komatsugawa1, Ken’ichi Fukamachi3, *
1Chitose Institute of Science and Technology, Graduate School of Science and Technology, Chitose, Japan
2Health Sciences University of Hokkaido, Tobetsu, Japan
3Chitose Institute of Science and Technology, Chitose, Japan
*Corresponding author. Email: k-fukama@photon.chitose.ac.jp
Corresponding Author
Ken’ichi Fukamachi
Available Online 30 April 2026.
DOI
10.2991/978-94-6239-638-8_10How to use a DOI?
Keywords
Basic Life Support; Mixed Reality; Sensor Devices; Raspberry Pi
Abstract

We have developed a system using Mixed Reality (MR) and sensor devices to aid Basic Life Support (BLS) self-training. Our system can provide BLS trainees with the real-time feedback of training score and post-training score visualization. It combines visual information provided by a MR device and physical input data such as chest compression depth and recoil obtained from sensor devices. Our system was utilized by a group of nurses (from novices to experts) to evaluate its usability and effectiveness. The result shows that it assists BLS trainees with consistent self-training and offers valuable feedback, especially through score visualization, though we found that there were problems with the visibility and usability of real-time feedback elements. This study suggests that our system can complement conventional On-the-Job Training (OJT) based BLS training and has potential for broader application in clinical education.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the Workshop on Computation: Theory and Practice (WCTP 2025)
Series
Atlantis Highlights in Computer Sciences
Publication Date
30 April 2026
ISBN
978-94-6239-638-8
ISSN
2589-4900
DOI
10.2991/978-94-6239-638-8_10How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Shunsuke Goto
AU  - Yoko Tsukamoto
AU  - Hiroshi Komatsugawa
AU  - Ken’ichi Fukamachi
PY  - 2026
DA  - 2026/04/30
TI  - Development of a BLS Self-Training Support System using MR and Sensor Devices
BT  - Proceedings of the  Workshop on Computation: Theory and Practice (WCTP 2025)
PB  - Atlantis Press
SP  - 137
EP  - 151
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6239-638-8_10
DO  - 10.2991/978-94-6239-638-8_10
ID  - Goto2026
ER  -