A cost-effective, ai-based portable heart monitoring device for early detection of cardiac anomalies.

Abstract

This project presents a cost-effective, AI-integrated portable cardiac monitoring device designed for early detection of cardiac anomalies. The system integrates multiple biomedical sensors—ECG, SpO₂, blood pressure, respiratory rate, and temperature—to continuously measure critical physiological parameters. An embedded AI framework analyzes multi-sensor data in real time, detecting abnormalities such as arrhythmias, hypoxia, hypertension, and irregular breathing patterns through sensor fusion. The device features a touch display for real-time waveform visualization, alerts, remote monitoring and telemedicine integration. Optional report printing supports clinical documentation. One of the key strength of the device is cost effectiveness by using ECG lead reduction using mathematical calculation and use of readily available modern components and sensors. Furthermore, the system can be extended with additional features such as wireless communication, mobile app, and AI-based cuff-less blood pressure estimation. The design prioritizes affordability and low power consumption, making it ideal for rural and resource-limited settings.