RT Journal Article
T1 Can a voice assistant help bystanders save lives? A feasibility pilot study chatbot in beta version to assist OHCA bystanders
A1 Otero Agra, Martín
A1 Jorge Soto, Cristina
A1 Cosido Cobos, Óscar Jesús
A1 Blanco Prieto, Jorge
A1 Alfaya Fernández, Cristian
A1 García Ordóñez, Enrique
A1 Barcala Furelos, Roberto
K1 Bystander CPR
K1 Chain of survival
K1 Chatbot
K1 Assisted-CPR
K1 Conversational assistant
K1 OHCA recognition
AB Objective: Evaluating the usefulness of a chat bot as an assistant during CPR care by laypersons. Methods: Twenty-one university graduates and university students naive in basic life support participated in this quasi-experimental simulation pilot trial. A version beta chatbot was designed to guide potential bystanders who need help in caring for cardiac arrest victims. Through a Question-Answering (Q&A) flowchart, the chatbot uses Voice Recognition Techniques to transform the user's audio into text. After the transformation, it generates the answer to provide the necessary help through machine and deep learning algorithms. A simulation test with a Laerdal Little Anne manikin was performed. Participants initiated the chatbot, which guided them through the recognition of a cardiac arrest event. After recognizing the cardiac arrest, the chatbot indicated the start of chest compressions for 2 min. Evaluation of the cardiac arrest recognition sequence was done via a checklist and the quality of CPR was collected with the Laerdal Instructor App. Results: 91% of participants were able to perform the entire sequence correctly. All participants checked the safety of the scene and made sure to call 112. 62% place their hands on the correct compression point. A media time of 158 s (IQR: 146–189) was needed for the whole process. 33% of participants achieved high-quality CPR with a median of 60% in QCPR (IQR: 9–86). Compression depth had a median of 42 mm (IQR: 33–53) and compression rate had a median of 100 compressions/min (IQR: 97–100). Conclusion: The use of a voice assistant could be useful for people with no previous training to perform de out-of-hospital cardiac arrest recognition sequence. Chatbot was able to guide all participants to call 112 and to perform continuous chest compressions. The first version of the chatbot for potential bystanders naive in basic life support needs to be further developed to reduce response times and be more effective in giving feedback on chest compressions
PB Elsevier
YR 2022
FD 2022
LK http://hdl.handle.net/10347/29402
UL http://hdl.handle.net/10347/29402
LA eng
NO The American Journal of Emergency Medicine 61 (2022) 169-174. https://doi.org/10.1016/j.ajem.2022.09.013
DS Minerva
RD 25 abr 2026