CPR Guardian: A Real-Time Digital Twin for CPR Rate and Depth Feedback

Overview

Out-of-hospital cardiac arrest survival depends on effective cardiopulmonary resuscitation (CPR), which maintains blood flow to the brain and vital organs. However, CPR quality often declines due to rescuer fatigue, leading to reduced compression depth and rate and decreased perfusion. This project evaluates whether a sensor-based system can quantify CPR quality and detect physiologically relevant performance decline in real time. A prototype system was developed using a Force-Sensitive Resistor (FSR) to estimate compression force as a proxy for depth, and a pulse sensor to monitor rescuer heart rate as an indicator of physical exertion. Data were processed through an Arduino Uno R4 WiFi and analyzed using a Python-based platform to compute compression rate (CPM), depth consistency, and a combined efficiency score. A fatigue model incorporating pulse trends and performance metrics was used to estimate when CPR effectiveness would decline below target thresholds. A digital twin interface provided real-time visualization and stored session data for analysis . A controlled test was conducted using a CPR manikin across adult, child, and infant modes under both feedback and no-feedback conditions (72 total sessions). Key physiological proxies analyzed included rate compliance, depth consistency, and fatigue progression over time . Results demonstrated progressive deterioration in CPR quality, with compression rate decreasing from ~110 CPM to below recommended levels and depth consistency declining as rescuer pulse BPM increased. Feedback-enabled sessions showed higher combined accuracy, suggesting improved maintenance of physiologically effective compressions. This project demonstrates that CPR performance decline can be quantified using mechanical and physiological indicators. Integrating real-time monitoring with predictive fatigue analysis may improve CPR effectiveness by supporting timely rescuer rotation and maintaining adequate perfusion during cardiac arrest.

Competition history

• CSEF 2026 Medicine & Physiology (Junior Division) · Entry J-15-10

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