Smartwatches as chest compression feedback devices: A feasibility study

Resuscitation. 2016 Jun;103:20-23. doi: 10.1016/j.resuscitation.2016.03.014. Epub 2016 Mar 19.

Abstract

Background: Recently, there have been attempts to use smartphones and smartwatches as the feedback devices to improve the quality of chest compressions. In this study, we compared chest compression depth feedback accuracy between a smartphone and a smartwatch in a hands-only cardiopulmonary resuscitation scenario, using a manikin with a displacement sensor system.

Methods: Ten basic life support providers participated in this study. Guided by the chest compression depths displayed on the monitor of a laptop, which received data from the manikin, each participant performed 2min of chest compressions for each target depth (35mm and 55mm) on a manikin while gripping a smartphone and wearing a smartwatch. Participants had a rest of 1h between the instances, and the first target depth was set at random. Each chest compression depth data value from the smartphone and smartwatch and a corresponding reference value from the manikin with the displacement system were recorded. To compare the accuracy between the smartphone and smartwatch, the errors, expressed as the absolute of the differences between the reference and each device, were calculated.

Results: At both target depths, the error of the smartwatch were significantly smaller than that of the smartphone (the errors of the smartphone vs. smartwatch at 35mm: 3.4 (1.3) vs. 2.1 (0.8) mm; p=0.008; at 55mm: 5.3 (2.8) vs. 2.3 (0.9) mm; p=0.023).

Conclusion: The smartwatch-based chest compression depth feedback was more accurate than smartphone-based feedback.

Keywords: CPR; Chest compression; Feedback device; Smartphone; Smartwatch.

Publication types

  • Randomized Controlled Trial
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Cardiopulmonary Resuscitation / methods*
  • Feasibility Studies
  • Feedback, Sensory*
  • Heart Massage / methods*
  • Humans
  • Male
  • Manikins
  • Mobile Applications
  • Prospective Studies
  • Smartphone / instrumentation*
  • Time Factors