Medical ECG Docking Station
Desktop application for continuous ECG data collection via BLE, with real-time monitoring and AWS cloud integration for AI-powered arrhythmia analysis.
The Challenge
Quoretech (USA) develops arrhythmia diagnosis solutions and needed a reliable desktop application for continuous ECG data collection. The system had to maintain stable BLE communication with wearable ECG sensors, perform real-time data logging, and transmit data to AWS for cloud-based AI analysis — all with medical-grade reliability.
Our Approach
We developed a desktop application in C++ with the Qt framework, designed for the demanding requirements of medical device data acquisition.
BLE Communication
The Qt Bluetooth module handles BLE communication with ECG wearable sensors. We implemented robust connection management with automatic reconnection, data integrity verification, and error recovery to ensure no data loss during long monitoring sessions.
Real-Time Logging & Transmission
ECG data is continuously logged locally while simultaneously streaming to AWS cloud infrastructure. TCP connections provide structured logging, and the system handles network interruptions gracefully with local buffering.
Monitoring & Diagnostics
DataDog integration provides real-time system monitoring — tracking connection stability, data throughput, and application health. This enables remote diagnostics and proactive maintenance.
Technical Stack
- Languages: C++
- Framework: Qt (Bluetooth, Network modules)
- Communication: BLE (Bluetooth Low Energy)
- Cloud: AWS (storage and AI analysis)
- Monitoring: DataDog
- Networking: TCP structured logging
Results
- Dependable BLE communication with zero data loss
- Continuous ECG data collection over extended monitoring periods
- Real-time cloud transmission for AI-powered arrhythmia analysis
- Remote monitoring and diagnostics capabilities