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Development of Robot Simulator for Interactive Training of Neonatal Cardio-Pulmonary Resuscitation

Y Takebe, K. Imamura, Yurina Sugamiya, Yuri Nakae, T. Katayama, Takuya Otani, Hiroyuki Ishii, Atsuo Takanishi

Year
2021
Citations
1

Abstract

In recent years, awareness of improving the quality of medical care has increased. We focused on neonatal resuscitation, which is difficult to train clinically, and our long-term goal is a neonatal resuscitation training system that can simulate cases and can feedback interactively based on quantitative evaluation of the procedures. In this study, we developed the neonatal simulator that has a respiratory movement simulating mechanism and a chest compression measurement mechanism. Through an interview with neonatologists, the fidelity of respiratory movements and the possibility of evaluating chest compression with the developed simulator were assessed.

Keywords

ResuscitationSimulationComputer scienceFidelityNeonatal resuscitationTraining (meteorology)High fidelityMechanism (biology)MedicineCardiopulmonary resuscitation

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