Real-Time ECG Monitoring & Visualization Platform graph

// tech stack

// about

Overview

This project is a real-time ECG monitoring and visualization platform designed to display continuous biosensor data for medical analysis. The system receives high-frequency ECG signals via WebSocket and renders them dynamically for doctors to analyze patient vitals over time.

Problem Statement

Handling continuous, high-frequency ECG data in real time presents multiple challenges:

• ▹Maintaining smooth UI rendering without performance lag
• ▹Handling network interruptions without losing data continuity
• ▹Synchronizing missed data accurately after reconnection
• ▹Providing precise time-based navigation for medical analysis

Solution

I designed and built a frontend system that ensures accurate, real-time ECG visualization with reliability and performance in mind.

Key Implementations

1. Real-Time Data Streaming

• ▹Integrated WebSocket-based communication to receive continuous ECG data streams
• ▹Managed high-frequency data updates efficiently to avoid UI blocking

2. Buffering & Network Recovery

• ▹Implemented a buffering mechanism to handle temporary network interruptions
• ▹Ensured data synchronization after reconnection to maintain continuity
• ▹Prevented data loss and visual inconsistencies during unstable connections

3. High-Performance Graph Rendering

• ▹Optimized rendering logic to handle continuous data updates smoothly
• ▹Avoided unnecessary re-renders for better performance
• ▹Ensured real-time responsiveness even with large data streams

4. Timeline-Based Navigation

• ▹Built an interactive timeline allowing users to select specific time ranges
• ▹Enabled doctors to analyze ECG data at precise timestamps

5. Multi-Metric Visualization

• ▹Integrated multiple medical data streams (ECG leads, vitals)
• ▹Displayed synchronized charts for comprehensive analysis

Impact

• ▹Enabled reliable real-time monitoring of patient ECG data
• ▹Improved system stability under network fluctuations
• ▹Delivered smooth and accurate visualization for medical decision-making

Key Learnings

• ▹Handling real-time systems requires careful performance optimization
• ▹Network instability must be considered as a primary design factor
• ▹Efficient data handling and rendering are critical for user experience in high-frequency systems