Holo-BLSD – A Holographic Tool for Self-training and Self-Evaluation of Emergency Response Skills

In case of cardiac arrest, prompt intervention of bystanders can be vital in saving lives. Basic Life Support and Defibrillation (BLSD) is a procedure designed to deliver a proficient emergency first response. Developing skills in BLSD in a large part of the population is a primary educational goal of resuscitation medicine. In this context, novel computer science technologies like Augmented Reality (AR) and Virtual Reality (VR) can alleviate some of the drawbacks of traditional instructor-led courses, especially concerning time and cost constraints. This paper presents Holo-BLSD, an AR system that allows users to learn and train the different operations involved in BLSD and receive an automatic assessment. The system uses a standard manikin which is “augmented” by an interactive virtual environment that reproduces realistic emergency scenarios. The proposed approach has been validated through a user study. Subjective results confirmed the usability of the devised tool and its capability to stimulate learners’ attention. Objective results indicated no statistical significance in the differences between the examiners’ evaluation of users who underwent traditional and AR training; they also showed a close agreement between expert and automatic assessments, suggesting that Holo-BLSD can be regarded as an effective self-learning method and a reliable selfevaluation tool.

[1]  Joost J L M Bierens,et al.  Self-training in the use of automated external defibrillators: the same results for less money. , 2008, Resuscitation.

[2]  David R. Michael,et al.  Serious Games: Games That Educate, Train, and Inform , 2005 .

[3]  Woontack Woo,et al.  Projected AR-Based Interactive CPR Simulator , 2013, HCI.

[4]  Alvaro Uribe-Quevedo,et al.  A Comparison of Seated and Room-Scale Virtual Reality in a Serious Game for Epidural Preparation , 2020, IEEE Transactions on Emerging Topics in Computing.

[5]  Wolfgang Effelsberg,et al.  Serious Games: Foundations, Concepts and Practice , 2016 .

[6]  Liyan Song,et al.  Digital Game-Based Learning , 2014 .

[7]  Audrey L. Blewer,et al.  Continuous chest compression cardiopulmonary resuscitation training promotes rescuer self-confidence and increased secondary training: A hospital-based randomized controlled trial* , 2012, Critical care medicine.

[8]  Niall McShane,et al.  Mapping Learning and Game Mechanics for Serious Games Analysis in Engineering Education , 2017, IEEE Transactions on Emerging Topics in Computing.

[9]  R S Kalawsky,et al.  VRUSE--a computerised diagnostic tool: for usability evaluation of virtual/synthetic environment systems. , 1999, Applied ergonomics.

[10]  Gavin D Perkins,et al.  AED training and its impact on skill acquisition, retention and performance--a systematic review of alternative training methods. , 2011, Resuscitation.

[11]  Alberto Del Bimbo,et al.  Natural and virtual environments for the training of emergency medicine personnel , 2014, Universal Access in the Information Society.

[12]  Jakob Nielsen,et al.  Usability engineering , 1997, The Computer Science and Engineering Handbook.

[13]  Antonio Frisoli,et al.  Motion detection technology as a tool for cardiopulmonary resuscitation (CPR) quality training: a randomised crossover mannequin pilot study. , 2013, Resuscitation.

[14]  Mario Muñoz Organero,et al.  Can Gamification Improve the Benefits of Student Response Systems in Learning? An Experimental Study , 2016, IEEE Transactions on Emerging Topics in Computing.

[15]  K. Monsieurs,et al.  Guidelines for Resuscitation 2015 ection 10 . Education and implementation of resuscitation , 2015 .

[16]  Wonjoon Kim,et al.  HeartiSense: a novel approach to enable effective basic life support training without an instructor , 2014, CHI Extended Abstracts.

[17]  Gyu Chong Cho,et al.  Effects of script-based role play in cardiopulmonary resuscitation team training , 2010, Emergency Medicine Journal.

[18]  William C. Mundell,et al.  Simulation technology for resuscitation training: a systematic review and meta-analysis. , 2013, Resuscitation.

[19]  J. B. Brooke,et al.  SUS: a retrospective , 2013 .

[20]  A. Frisoli,et al.  Kids (learn how to) save lives in the school with the serious game Relive. , 2017, Resuscitation.

[21]  Isabel Harb Manssour,et al.  Experiences using Augmented Reality Environment for training and evaluating medical students , 2013, 2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW).

[22]  J. B. Brooke,et al.  SUS: A 'Quick and Dirty' Usability Scale , 1996 .

[23]  James E. Driskell,et al.  Games, Motivation, and Learning: A Research and Practice Model , 2002 .

[24]  Panos Vardas,et al.  European Society of Cardiology: Cardiovascular Disease Statistics 2017. , 2018, European heart journal.

[25]  Hidehiko Hayashi,et al.  Development and evaluation of a corrective feedback system using augmented reality for the high-quality cardiopulmonary resuscitation training , 2017, 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[26]  Christos Gatzidis,et al.  Learning with Digital Games: A Practical Guide to Engaging Students in Higher Education , 2012, Int. J. Game Based Learn..

[27]  Monique L. Anderson,et al.  Regional Variation in Out-of-Hospital Cardiac Arrest Survival in the United States , 2015, Circulation.

[28]  Mich.,et al.  The effect of bystander CPR on survival of out-of-hospital cardiac arrest victims. , 1985, American heart journal.

[29]  Mateu Sbert,et al.  A Kinect-Based System for Cardiopulmonary Resuscitation Simulation: A Pilot Study , 2013, SGDA.

[30]  J. Keller Development and use of the ARCS model of instructional design , 1987 .

[31]  Roland Klemke,et al.  Effects of Game Design Patterns on Basic Life Support Training Content , 2013, J. Educ. Technol. Soc..