Multimodal Feedback in Automated Training Systems for Cardiopulmonary Resuscitation: A Review

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Authors: Mine Saraç, Şevval Çetin, Baran Aslan, Ali Tas, Fabio Stroppa
Cited by: 0
References: 103

Abstract

Incorporating multimodal feedback in automated cardiopulmonary resuscitation (CPR) training systems has emerged as a crucial advancement in medical education, aiming to improve the quality and efficacy of CPR performance. This work presents an extensive and technical literature search on automated training CPR systems, specifically focusing on the feedback modality they provide during training sessions. We completed the search in the IEEE, ACM, Springer, SAGE, Elsevier, MDPI, Scholar, and Scopus databases between 2015 and 2025 (August) using the keywords “CPR,” “Virtual Reality (VR),” “Augmented Reality (AR),” “feedback,” and “training.” We categorized our findings based on the type of feedback provided (i.e., visual, audio, haptic, or a combination of these), the display type used to render the feedback, the technology used to monitor the trainee’s performance, and the type of manikin used. We conclude with recommendations for future research.

Fields of Study & Subjects

Cardiac Arrest and Resuscitation Simulation-Based Education in Healthcare Augmented Reality Applications

Publication details

Journal / source
IEEE Transactions on Human-Machine Systems
Volume
56
Issue
2
Pages
410–424
Publication date
12 January 2026