As most of us working in health care training know, we sometimes have to rely on creating or hacking trainers to better suit the needs of the program and the learners. One of the newest projects I have been working on includes upgrading a CPR manikin to include a CPR feedback device made with Arduino. There are plenty of CPR feedback devices available on the market, some use a cell-phone, a portable device, or a CPR manikin with these features included. This project was not meant to create something entirely new but to evaluate more cost-effective ways to build upon existing trainers.

This project involves upgrading a standard CPR Manikin into a smart training tool with a CPR Feedback Device system developed on the Arduino platform, which will help assess the efficiency of a learner's chest compressions in real-time, focusing on cost-effectiveness and flexibility in use.

System Features

The CPR feedback device is designed to support CPR standards (AHA Guidelines) and consists of the following key functions:

Real Time Rate Measurement: Calculates the chest compression rate (compressions per minute) to ensure it stays within the 100-120 compressions per minute guideline.
Depth Indicator: Measures the depth of chest compressions to check if the force is deep enough to stimulate blood circulation (typically 2 - 2.4 inches).
Time: Displays the total time spent on resuscitation.
Chest Recoil Indicator: Detects chest recoil, which is crucial for the heart to fully expand and receive blood before the next compression.
CPR Cycle Counter: Counts the number of CPR Cycles for accurate practitioner rotation.
9v Battery Powered: Supports a 9V battery power source, making it a portable and convenient device for any situation.
Scalable Design: The Code and Hardware architecture is designed to support future sensor upgrades, making it scalable and ready for future updates via code and sensors.

Engineering Details and System Operation

1. Hardware Analysis

From an engineering perspective, measuring depth and chest recoil can be achieved through various methods. However, this project focuses on accuracy and cost-effectiveness:

Microcontroller: Arduino (e.g., Nano or Uno) is chosen as the main processing unit due to its diverse Libraries and low power consumption.
Distance Sensor: To measure Depth and Recoil, high-resolution distance sensors such as an Ultrasonic Sensor (HC-SR04) or a Time-of-Flight (ToF) Sensor (e.g., VL53L0X) are typically chosen. These are installed at the top or inside the manikin to detect the movement range of the chest during compression.
Display: An OLED or I2C LCD screen is used to show various statistics, allowing learners to immediately see errors.

2. Code Logic

To obtain accurate readings, the program operates in coordination as follows:

Rate Calculation: The system uses the timing function (millis()) to measure the Interval between each compression, then divides it to convert into Beats Per Minute (BPM). If the rate falls outside the 100-120 BPM range, the system will provide an alert.
Depth Measurement: The program records the initial distance (Baseline). When a compression occurs, the display shows the difference in distance (Current Distance - Baseline), which must pass through signal Filtering to prevent fluctuations.
Chest Recoil Detection: This is the most challenging part. The logic checks if the distance returns to the Baseline value after a compression. If the learner is still Leaning on the chest, the system will alert them to fully release their hands.
Cycle Counter: When the system detects 30 compressions (in the case of a 30:2 simulation) or according to a set time, it records this as 1 Cycle.

3. Power Management

Since a 9V battery is required, the system manages power through the Voltage Regulator on the Arduino board to supply stable power to the distance sensor, which is highly sensitive to voltage.

Conclusion and Future Possibilities

Building a CPR Feedback Device with Arduino is not just about cost savings; it's about creating a tool capable of Data Logging for retrospective analysis. In the future, we can add a Bluetooth module (e.g., HC-05) to transmit data to smartphones, or add a Ventilation force sensor to make it an even more complete training device.

This project demonstrates that "Low-cost technology," when combined with "precise engineering," can create life-saving innovations in the world of medical education.