Development of a portable 3 -lead ECG device with mobile integration for cardiac monitoring & early detection of cardiovascular disease

Development of a portable 3 -lead ECG device with mobile integration for cardiac monitoring & early detection of cardiovascular disease

Development of a portable 3 -lead ECG device with mobile integration for cardiac monitoring & early detection of cardiovascular disease
A major cause behind high heart-related fatalities is late diagnosis due to the bulk, high cost, and limited accessibility of traditional hospital ECG machines. Developed to bridge the gap between the sudden onset of symptoms and timely clinical testing, this capstone project introduces a compact, affordable, and intelligent "Pocket ECG" system. The device enables everyday users to capture diagnostic-quality heart electrical activity anywhere, at any time, promoting proactive and preventive healthcare.
Key Features & InnovationIntelligent AI Analysis Layer:
Employs a pre-trained Convolutional Neural Network (CNN) model trained on clinical datasets (such as MIT-BIH and PTB). The AI evaluates short segments of the incoming ECG stream to accurately classify cardiac rhythms (e.g., Normal Sinus vs. Arrhythmias). Automated Comprehensive Reporting: Instantly generates an exportable health summary that includes raw/filtered waveform graphs, heart rate variability, and AI-driven classification flags.
Integrated Healthcare Ecosystem: Includes localized doctor recommendation tools, appointment booking capabilities, and automated SMS/Email alerts via Twilio or SendGrid for critical cardiac anomalies.
Personalized Wellness Guidance: Provides users with customized diet, lifestyle, and exercise recommendations tailored specifically to their recorded heart health metrics.