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This project measures the electrical activity of the heart using an AD8232 ECG Sensor Module connected to an Arduino Uno. The system relies on ECG electrodes and leads attached to the body to pick up minute bio-potential signals generated by heart muscle contractions. Because these electrical signals are extremely weak and susceptible to ambient noise, the AD8232 acts as an integrated signal conditioning block. It features an instrumentation amplifier to pull out the precise cardiac differential signals while rejecting common-mode noise, followed by operational amplifiers that provide active filtering and gain. Once conditioned, the analog output of the AD8232 is routed to one of the Arduino's analog input pins. The Arduino board runs a program developed in the Arduino IDE to continuously sample this analog voltage stream. By reading these values over time, the system can map out the characteristic P-Q-R-S-T waveform of a heartbeat. Developers can then process this digital stream of data to monitor heart rate, evaluate heart rate variability, or display the real-time electrocardiogram waveform visually using software tools.
Why Build This
Gain practical undergraduate-level experience in biomedical instrumentation and bio-potential signal acquisition.
Develop embedded firmware algorithms for filtering, peak detection, and real-time waveform analysis on resource-constrained microcontrollers.
Explore the hardware-level implementation of biomedical telemetry systems suitable for fitness trackers and remote patient monitoring prototypes.
Real-World Application
Biomedical health monitoring, patient telemetry, fitness trackers, and early cardiac anomaly detection such as arrhythmias or myocardial infarction symptoms.
Skills You'll Learn
Bio-potential signal acquisition
analog instrumentation amplification
noise reduction and filtering
analog-to-digital conversion
biomedical waveform analysis
Safety Precautions
Ensure proper electrical isolation and avoid direct mains power connection when using body-attached bio-potential sensors to prevent safety hazards.
Technology Tags
ARDUINO
AD8232
ECG SENSOR
BIOMEDIAL
SENSORS
HEALTH MONITORING
C++
SIGNAL PROCESSING
Frequently Asked Questions
Ensure proper electrical isolation and avoid direct mains power connection when using body-attached bio-potential sensors to prevent safety hazards.
ECG signals are extremely small (millivolts), meaning poor electrode skin contact, movement artifacts, or loose lead wire connections will easily disrupt or obscure the waveform.
No, this project is designed for educational exploration, prototyping, and engineering telemetry practice, not for medical diagnosis or clinical use.
Gallery
This page is part of Kitkraft's Project Hub — a curated collection of electronics & robotics projects gathered from the maker community to help students and hobbyists discover and learn to build. Kitkraft does not claim authorship of the original project, and makes no representation as to the accuracy, completeness or safety of third-party source material. The summary and "How It Works" explanation above are AI-generated, rewritten with reference to the original tutorial — not a reproduction of it. Full credit and a direct link to the original source are provided above. If you're the original creator and have a concern about how your work is represented here, please contact us and we'll address it promptly.
Jumper Wire 10 Pin Male To Male 20cm
Rs. 45.00
400 Points Mini Solderless Prototype PCB Breadboard High Quality
Rs. 89.00
MB102 Adjustable Breadboard Power Supply Module (3.3V & 5V) for Arduino & Raspberry Pi
Rs. 139.00
Jumper Wire 10 Pin Male To Female 20cm
Rs. 45.00
