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Traditional cardiopulmonary resuscitation training does not allow learners to accurately grasp power, depth and frequency. Therefore, this study aims to improve traditional training and reduce training volume, weight and price by using VR-CPRs learning support system. This study also provide immersive learning at a price lower than that currently prevalent in the market to impart the same level of learning and make CPR training more common. Our system makes it easier for individuals to learn cardiopulmonary resuscitation, making cardiopulmonary resuscitation training more common. Our system includes video health education, assisted real-time interactive operation tools, learning tests and other self-learning functions. Learners can practice on their own after watching the training film. The system reverberates the learner's power and frequency through a force-sensitive model to ensure that they are properly trained. Encourage users to learn CPR skills through immersive virtual reality settings that guide somatosensory interactions and support game-based learning. The study collected 100 college students who had never received CPR training. Before performing cardiopulmonary resuscitation on the force-sensitive model, participants were asked to complete a pre-test questionnaire to obtain pre-intervention learning outcomes. We introduced VR-CPR into CPR learning (intervention), assessed the outcome of the intervention, and asked participants to complete a post-test questionnaire. The study used VR-CPR to intensively study 85% of participants, indicating that the system is effective in promoting CPR learning, cultivating CPR learning interest, and improving public CPR ability.

Trends in digital games and game-based learning development are gradually moving toward physical interactivity and man-machine experiential input. In this study, a motion-sensing wireless handle created by the Industrial Technology Research Institute of Taiwan was applied to a PC-based digital somatosensory learning system. Through wireless signal transmission, a decision tree algorithm was used to verify and analyze the information for determining the corresponding functions and motion-sensing identification. The enhanced accuracy and validity rate of action judgments of physical action signals (action-end device) sent to the somatosensory system can increase the efficiency of instant interaction and fluency between the interface and game system. The research results can be used to develop somatosensory games, add to the collective knowledge in this field, and improve future system efficacy. This study can help developers working on digital games and in other related fields to understand the engines and hardware principles of somatosensory games. Moreover, because ideas are presented without excessive complexity, the results may encourage students to develop somatosensory games.