Training CPR with a Wearable Real Time Feedback System

Agnes Grünerbl, Hamraz Javaheri, Eloise Monger, Mary Gobbi, Paul Lukowicz

In: Proceedings of the IEEE International Symposium on Wearable Computers. IEEE International Symposium on Wearable Computers (ISWC-2018) October 8-12 Singapore Singapore Seiten 44-47 ISBN 978-1-4503-5967-2/18/10 ACM 2018.


We present a study comparing the effect of real-time wearable feedback with traditional training methods for cardiopulmonary resuscitation (CPR). The aim is to ensure that the students can deliver CPR with the right compression speed and depth. On the wearable side, we test two systems: one based on a combination of visual feedback and tactile information on a smart-watch and one based on visual feedback and audio information on a Google Glass. In a trial with 50 subjects (23 trainee nurses and 27 novices,) we compare those modalities to standard human teaching that is used in nurse training. While a single traditional teaching session tends to improve only the percentage of correct depth, it has less effect on the percentage of effective CPR (depth and speed correct at the same time). By contrast, in a training session with the wearable feedback device, the average percentage of time when CPR is effective improves by up to almost 25%.

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence