End-to-End Integration Testing of a Regulated Medical Device
End-to-end integration testing for GE Healthcare’s wireless patient monitoring sensors, validating the complete data path from patient-worn sensors to the nursing station before market launch.
Built to validate the complete sensor-to-clinical data path.
AMSA developed and maintained an end-to-end integration testing framework and Hardware-in-the-Loop infrastructure to validate connectivity, data integrity and system behaviour before release.
Custom HIL Test Racks
Macroboard-based test racks exposed sensor, battery and Yocto hub interfaces for controlled probing and monitoring.
End-to-End Validation
Testing validated data delivery from patient-worn sensors through the MBAN and Yocto Linux hub to the nursing station.
Adverse Conditions
Link regression, wireless attenuation, association and multi-sensor scenarios reproduced real-world system conditions.
Event-Based Testing
A Python-based event framework enabled hundreds of automated test cases and parallel execution across multiple sensor types.
Built around hardware-in-the-loop testing and end-to-end system validation.
The testing environment combined custom HIL infrastructure, protocol-level analysis and automated test execution to validate connectivity, data integrity and system behaviour across the complete sensor data path.
Python
Test Automation
HIL Test Racks
Macroboard-based Infrastructure
UART / SPI
Protocol Sniffing
Wireshark
Packet-level Analysis
Event-based Testing
Test Framework Design
Python
Test Automation
HIL Test Racks
Macroboard-based Infrastructure
UART / SPI
Protocol Sniffing
Wireshark
Packet-level Analysis
Event-based Testing
Test Framework Design
Parallel Execution
Automated Test Execution
Wireless Attenuation
Real-world Condition Simulation
MBAN
Medical Body Area Network
Yocto Linux
Handheld Hub Platform
Parallel Execution
Automated Test Execution
Wireless Attenuation
Real-world Condition Simulation
MBAN
Medical Body Area Network
Yocto Linux
Handheld Hub Platform
The framework enabled automated validation across connectivity, data integrity and system behaviour, with hundreds of test cases executed across multiple sensor types.
Reducing release risk through end-to-end validation.
The testing framework helped identify connectivity, alarm-handling and data-integrity issues early, giving the development team time to resolve defects before release.
Early Defect Detection
End-to-end testing surfaced issues across connectivity, alarm handling and data integrity before release.
Data Integrity Validation
Packet capture and Wireshark analysis provided packet-level verification of data delivery across the system.
Reduced Release Risk
Validating the complete data path helped reduce the risk of defects reaching the market during the lead-up to launch.
Release Confidence
The validated end-to-end data-delivery pipeline supported a reliable first market launch for the wireless patient monitoring sensors.
