Automated LabVIEW Testing for Accelerated CPAP/BiPAP Device Verification
March 4, 2026
7 Key Women’s Health Issues in India: PCOS, Fertility, Menopause & Daily Wellness
April 16, 2026Automated LabVIEW Testing for Accelerated CPAP/BiPAP Device Verification
March 4, 20267 Key Women’s Health Issues in India: PCOS, Fertility, Menopause & Daily Wellness
April 16, 2026Automated Medical Device Validation Using LabVIEW & NI DAQ for EMG-EIM Diagnostic Systems
About Client
A leading medical technology company, working in collaboration with top hospitals and neurology departments across the USA and Europe. The client specializes in advanced diagnostic devices for neuromuscular and neurophysiological disorders, with a strong focus on precision, compliance and clinician usability. Their initiatives are strongly driven by medical product engineering innovations aimed at improving diagnostic accuracy and clinical outcomes.
Client's Challenge
The client was developing an advanced EMG–EIM diagnostic platform that combines analog signal acquisition, FPGA processing, and system-level software to analyze physiological signals. Ensuring the accuracy and reliability of the entire signal chain—from the analog front end to algorithm processing and data communication—was critical for clinical performance and regulatory compliance.
However, validating complex EMG and impedance signals across multiple hardware and software layers was challenging with conventional testing methods. The client needed a structured and repeatable testing framework capable of generating controlled signals, independently verifying system outputs, and producing traceable validation results aligned with medical device regulatory requirements.
iORBIT Solution Approach
To ensure performance, safety, and regulatory compliance, iOrbit adopted a structured and robust medical device validation and software testing approach, aligned with established healthcare application testing methodologies.
As part of this strategy, LabVIEW and NI DAQ were implemented as an automated verification and validation (V&V) framework for the EMG–EIM diagnostic platform. This architecture enabled repeatable testing, independent signal verification, and structured validation workflows aligned with regulatory expectations for medical device software and system-level validation.
System Architecture for Medical Device Software Testing
Device Under Test (DUT)
The EMG–EIM system consists of:
- Analog Front End (AFE)
- FPGA processing modules
- Processing System (PS)
- PC-based validation environment
The validation setup interfaced with multiple signal nodes across the hardware and software stack, supporting comprehensive medical device software testing and system-level validation.
Using LabVIEW-controlled NI DAQ hardware, calibrated reference signals were injected into the AFE while internal processing outputs were captured for independent verification.
Automated validation frameworks should also align with regulatory expectations such as guidance from the FDA on the General Principles of Software Validation, ensuring medical device software is properly verified and validated before market release.
This architecture reflects modern medical device validation services practices used in regulated healthcare environments.
EMG Signal Verification & Validation - Healthcare Application Testing Approach
For EMG verification & validation:
- LabVIEW generated representative EMG waveforms.
- Signals were injected into the EMG instrumentation amplifier.
- The AFE digitized signals through ADC conversion.
- FPGA EMG algorithms processed incoming data.
- Processed data was transmitted via UART to the PC.
LabVIEW received data using VISA serial communication and performed independent analysis to validate:
- Signal integrity
- Gain accuracy
- Filtering performance
- Timing synchronization
- Noise characteristics
This workflow demonstrates practical healthcare application testing applied to physiological signal acquisition systems.
EIM Signal Validation - Automated Medical Device Validation Methodology
For Electrical Impedance Myography (EIM):
- NI DAQ generated controlled stimulus voltage and current signals.
- LabVIEW controlled amplitude, frequency and test sequencing.
- Validation included:
- Single-frequency Guide Mode
- Multi-frequency Analysis Mode
Captured signals were processed by FPGA algorithms and transferred to the Processing System for impedance computation.
LabVIEW independently validated:
- Impedance calculations
- Frequency response behaviour
- Signal stability
- Noise performance
This robust workflow demonstrates a practical and systematic approach to healthcare application testing, specifically applied to high-precision physiological signal acquisition and diagnostic MedTech systems.
UART Data Acquisition and Independent Software Verification
LabVIEW functioned as an external verification platform by:
- Receiving EMG and EIM data via UART using VISA communication.
- Decoding structured data packets.
- Reconstructing numeric datasets.
- Performing real-time visualization and analysis.
Separating the analysis environment from the device ensured unbiased verification - a key requirement in professional medical device software testing workflows.
Usability Risk Testing of Medical Devices Through Automated Validation
Beyond signal verification, automated testing supported Usability Risk Testing of Medical Devices by enabling:
- Repeatable clinical signal simulations
- Failure condition testing
- Performance boundary evaluation
- Algorithm robustness verification
Such validation reduces user-interaction risks and strengthens regulatory compliance readiness.
End-to-End Medical Device Validation Coverage
The LabVIEW + NI DAQ framework enabled complete verification coverage across:
- Analog acquisition chain
- FPGA signal processing
- Impedance algorithms
- Software data handling
- Communication interfaces
Automation improved traceability, repeatability and validation confidence - core deliverables expected from professional medical device validation services.
Scalable Healthcare Application Testing Strategy
Automated testing platforms can significantly accelerate medical device validation, improve medical device software testing efficiency, and enable scalable healthcare application testing for next-generation diagnostic systems.
A LabVIEW-based validation framework provides a reusable and structured testing environment that supports regulatory submissions, improves product reliability, and helps accelerate MedTech commercialization.
Conclusion
Through the implementation of an automated validation framework using LabVIEW and NI DAQ, iOrbit successfully established a structured and scalable verification environment for the EMG–EIM diagnostic platform.
The solution enabled reliable signal generation, independent verification of system outputs, and repeatable automated testing across the analog front end, FPGA processing, and system-level software components. This significantly improved validation coverage, test traceability, and confidence in system performance.
As a result, the client benefited from a robust validation framework that strengthened regulatory readiness, improved product reliability, and accelerated the overall development and validation cycle for their advanced diagnostic platform.
FAQ - Medical Device Validation Using LabVIEW & NI DAQ
1.What are the benefits of using LabVIEW for medical device validation?
Using LabVIEW for medical device validation enables automated test execution, real-time signal analysis, scalable test frameworks, and improved verification coverage across hardware and software components.
2. Why is LabVIEW commonly used in medical device testing?
LabVIEW provides a graphical programming environment that enables engineers to automate signal generation, data acquisition, and analysis, making it suitable for verification and validation of complex diagnostic devices.
3. How does NI DAQ support automated validation workflows?
NI DAQ hardware enables precise signal generation and high-accuracy data acquisition, allowing engineers to simulate physiological signals and validate system responses under controlled test conditions.