A Development of a Sound Recognition-Based Cardiopulmonary Resuscitation Training System.

The objective of this study was to develop a sound recognition-based cardiopulmonary resuscitation (CPR) training system that is accessible, cost-effective, easy-to-maintain and provides accurate CPR feedback. Beep-CPR, a novel device with accordion squeakers that emit high-pitched sounds during compression, was developed. The sounds emitted by Beep-CPR were recorded using a smartphone, segmented into 2-second audio fragments, and then transformed into spectrograms. A total of 6,065 spectrograms were generated from approximately 40 minutes of audio data, which were then randomly split into training, validation, and test datasets. Each spectrogram was matched with the depth, rate, and release velocity of the compression measured at the same time interval by the ZOLL X Series monitor/defibrillator. Deep learning models utilizing spectrograms as input were trained using transfer learning based on EfficientNet to predict the depth (Depth model), rate (Rate model), and release velocity (Recoil model) of compressions. Results: The mean absolute error (MAE) for the Depth model was 0.30 cm (95% confidence interval [CI]: 0.27-0.33). The MAE of the Rate model was 3.6/min (95% CI: 3.2-3.9). For the Recoil model, the MAE was 2.3 cm/s (95% CI: 2.1-2.5). External validation of the models demonstrated acceptable performance across multiple conditions, including the utilization of a newly-manufactured device, a fatigued device, and evaluation in an environment with altered spatial dimensions. We have developed a novel sound recognition-based CPR training system, that accurately measures compression quality during training. Significance: Beep-CPR is a cost-effective and easy-to-maintain solution that can improve the efficacy of CPR training by facilitating decentralized at-home training with performance feedback.

Three-year trends in out-of-hospital cardiac arrest across the world: Second report from the International Liaison Committee on Resuscitation (ILCOR).

BACKGROUND: The International Liaison Committee on Resuscitation (ILCOR) Research and Registries Working Group previously reported data on systems of care and outcomes of out-of-hospital cardiac arrest (OHCA) in 2015 from 16 national and regional registries. To describe the temporal trends with updated data on OHCA, we report the characteristics of OHCA from 2015 through 2017. METHODS: We invited national and regional population-based OHCA registries for voluntary participation and included emergency medical services (EMS)-treated OHCA. We collected descriptive summary data of core elements of the latest Utstein style recommendation during 2016 and 2017 at each registry. For registries that participated in the previous 2015 report, we also extracted the 2015 data. RESULTS: Eleven national registries in North America, Europe, Asia, and Oceania, and 4 regional registries in Europe were included in this report. Across registries, the estimated annual incidence of EMS-treated OHCA was 30.0-97.1 individuals per 100,000 population in 2015, 36.4-97.3 in 2016, and 40.8-100.2 in 2017. The provision of bystander cardiopulmonary resuscitation (CPR) varied from 37.2% to 79.0% in 2015, from 2.9% to 78.4% in 2016, and from 4.1% to 80.3% in 2017. Survival to hospital discharge or 30-day survival for EMS-treated OHCA ranged from 5.2% to 15.7% in 2015, from 6.2% to 15.8% in 2016, and from 4.6% to 16.4% in 2017. CONCLUSION: We observed an upward temporal trend in provision of bystander CPR in most registries. Although some registries showed favourable temporal trends in survival, less than half of registries in our study demonstrated such a trend.