Smartwatch feedback device for high-quality chest compressions by a single rescuer during infant cardiac arrest: a randomized, controlled simulation study

Eur J Emerg Med. 2019 Aug;26(4):266-271. doi: 10.1097/MEJ.0000000000000537.

Abstract

Objective: According to the guidelines, rescuers should provide chest compressions (CC) ~1.5 inches (40 mm) for infants. Feedback devices could help rescuers perform CC with adequate rates (CCR) and depths (CCD). However, there is no CC feedback device for infant cardiopulmonary resuscitation (CPR). We suggest a smartwatch-based CC feedback application for infant CPR.

Participants and methods: We created a smartwatch-based CC feedback application. This application provides feedback on CCD and CCR by colour and text for infant CPR. To evaluate the application, 30 participants were divided randomly into two groups on the basis of whether CC was performed with or without the assistance of the smartwatch application. Both groups performed continuous CC-only CPR for 2 min on an infant mannequin placed on a firm table. We collected CC parameters from the mannequin, including the proportion of correct depth, CCR, CCD and the proportion of correct decompression depth.

Results: Demographics between the two groups were not significantly different. The median (interquartile range) proportion of correct depth was 99 (97-100) with feedback compared with 83 (58-97) without feedback (P = 0.002). The CCR and proportion of correct decompression depth were not significantly different between the two groups (P = 0.482 and 0.089). The CCD of the feedback group was significantly deeper than that of the control group [feedback vs. control: 41.2 (39.8-41.7) mm vs. 38.6 (36.1-39.6) mm; P=0.004].

Conclusion: Rescuers who receive feedback of CC parameters from a smartwatch could perform adequate CC during infant CPR.

Publication types

  • Randomized Controlled Trial

MeSH terms

  • Cardiopulmonary Resuscitation / methods*
  • Feedback*
  • Heart Arrest / therapy*
  • Humans
  • Infant
  • Korea
  • Manikins
  • Pressure
  • Prospective Studies
  • Simulation Training / methods*
  • Smartphone
  • Statistics, Nonparametric