IoT-Based Dual-Lead ECG Device with Mathematical Six-Lead Computation for Real-Time Continuous Monitoring
Electrocardiography (ECG) is essential for monitoring heart health, yet millions worldwide suffer from cardiac issues due to late diagnosis and lack of accessible monitoring. Traditional ECG machines, commonly used in Bangladesh, rely on paper-based printouts, which offer no digital tracking or real-time analysis. These machines, often costing around 50,000 BDT, limit accessibility, especially in resource-constrained settings.
In an era of AI-driven healthcare and IoT automation, ECG technology needs a revolution. Recognizing this gap, a team of Biomedical Engineering students from BME 7—Samir Fazal, Irfan Ahmed Rifat, and Samia Jahan—under the guidance of Principal Investigator Md. Tohibul Islam, has developed an affordable, IoT-enabled ECG device.
This innovative device offers real-time, continuous cardiac monitoring, enabling early detection of heart abnormalities using the Pan-Tompkins algorithm. By leveraging IoT connectivity with PHP and Firebase as its backend, it ensures seamless data tracking, secure patient data storage, and remote accessibility. To simplify the circuit and reduce costs, lead calculations were optimized, allowing the derivation of six additional leads from real-time dual-lead data using Einthoven’s rule. This makes the device highly efficient and cost-effective.
Designed for widespread use, the device can be deployed in remote areas, army camps, and even households for routine monitoring. Patients can easily share their ECG data with doctors via a secure, auto-generated link, enabling global remote access for medical professionals. This project received a grant from the Centre of Army Research and Development (CARD) for its development. Additionally, Chief of Army Staff General Waqar-uz-Zaman SBP OSP SGP psc personally visited and witnessed a live demonstration of the device in action.
Research Team
- Lecturer, Md. Tohibul Islam (Principal Investigator)
Department of Biomedical Engineering, MIST
- Samir Fazal, Irfan Ahmed Rifat, and Samia Jahan (BME-7)
Department of Biomedical Engineering, MIST