AI-Powered Cuffless Cardiovascular Monitoring

The Challenge

Traditional cardiovascular monitoring relies on bulky equipment and cuff-based blood pressure measurements, making continuous monitoring inconvenient. The goal of this project was to build a smart wearable healthcare device capable of collecting physiological data and preparing it for AI-driven analysis.

What We Built

An intelligent wearable platform capable of continuously monitoring:

• ECG (Electrocardiogram)
• Heart Rate (HR)
• Blood Oxygen Saturation (SpO₂)
• Motion & Activity Tracking
• Real-time Wireless Health Data Streaming

AI & Intelligent Healthcare Integration

Rather than simply collecting sensor data, the system is designed to become an Edge AI healthcare platform capable of intelligent decision-making.

AI Features Integrated

• AI-ready biomedical signal acquisition
• Real-time physiological data preprocessing
• Motion artifact reduction using sensor fusion
• Feature extraction from ECG and PPG signals
• Intelligent anomaly detection pipeline
• Continuous health trend analysis
• AI-compatible data pipeline for cloud or edge deployment

The architecture is designed to support machine learning models for:

• Arrhythmia Detection
• Heart Disease Risk Prediction
• Early Cardiovascular Event Detection
• Personalized Health Monitoring
• Predictive Analytics

Performance Metrics

• Heart Rate Accuracy: < 3% Error
• SpO₂ Accuracy: ±2%
• BLE Communication Latency: < 200 ms
• Stable Real-Time Monitoring

AI + IoT in Healthcare

This project demonstrates how Embedded AI and AIoT can transform traditional medical devices into intelligent healthcare assistants.

Potential applications include:

• Remote Patient Monitoring
• Smart Healthcare Wearables
• AI-Assisted Clinical Decision Support
• Predictive Health Analytics
• Cloud-Based Medical Monitoring
• Early Disease Detection