Yeongtak Song1, Youngjoon Chee2, Jaehoon Oh3, Chiwon Ahn4, Tae Ho Lim3. 1. Convergence Technology Center for Disaster Preparedness, Hanyang University, Seoul, Republic of Korea. 2. School of Electrical Engineering, University of Ulsan, Ulsan, Republic of Korea. Electronic address: yjchee@ulsan.ac.kr. 3. Convergence Technology Center for Disaster Preparedness, Hanyang University, Seoul, Republic of Korea; Department of Emergency Medicine, College of Medicine, Hanyang University, Seoul, Republic of Korea. 4. Department of Emergency Medicine, College of Medicine, Hanyang University, Seoul, Republic of Korea.
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.
RCT Entities:
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.
Authors: Bernhard Rössler; Julius Goschin; Mathias Maleczek; Felix Piringer; Rainer Thell; Martina Mittlböck; Karl Schebesta Journal: PLoS One Date: 2020-02-13 Impact factor: 3.240
Authors: Boram Choi; Taerim Kim; Sun Young Yoon; Jun Sang Yoo; Ho-Jeong Won; Kyunga Kim; Eun Jin Kang; Hee Yoon; Sung Yeon Hwang; Tae Gun Shin; Min Seob Sim; Won Chul Cha Journal: Healthc Inform Res Date: 2019-10-31
Authors: Chiwon Ahn; Seungjae Lee; Jongshill Lee; Jaehoon Oh; Yeongtak Song; In Young Kim; Hyunggoo Kang Journal: Int J Environ Res Public Health Date: 2021-05-19 Impact factor: 3.390