Smart Manikin for CardioPulmonary Resuscitation

Area of Science:

• Medical Education
• Biomedical Engineering
• Emergency Medicine

Background:

• Sudden cardiac arrest is a global health challenge requiring effective CardioPulmonary Resuscitation (CPR) training.
• Current CPR training faces limitations due to instructor-to-trainee ratios and reliance on subjective visual assessment.
• Existing CPR manikins are often passive, costly, or closed-source, hindering widespread adoption and quality.

Purpose of the Study:

• To introduce an open-source smart manikin with Technology-Enhanced Feedback (TEF) for autonomous CPR training.
• To provide accurate, consistent, and real-time feedback on key CPR metrics.
• To explore future capabilities for adaptive training and advanced life support scenarios.

Main Methods:

• Development of a smart CPR manikin integrated with TEF.
• Implementation of sensors to measure ventilation volume, compression depth, and chest recoil.
• Design of an autonomous system for real-time performance feedback.

Main Results:

• The smart TEF manikin provides autonomous, accurate, and consistent feedback on CPR performance.
• It objectively measures critical CPR metrics: ventilation volume, compression depth, and chest recoil.
• The manikin is open-source, addressing limitations of current technology.

Conclusions:

• The developed smart TEF manikin has the potential to significantly improve the quality and availability of CPR training.
• Autonomous, objective feedback can overcome limitations of traditional training methods.
• Future Human-in-the-Loop integration promises personalized training and advanced skill assessment, ultimately aiming to save lives from out-of-hospital cardiac arrest.