Introduction
Medical devices depend heavily on the software running inside them. It can be a wearable heart monitor, a blood pressure machine, or a hospital-grade ventilator, the software must work accurately and reliably. In this domain, even a small bug in the code or a missed test case could lead to incorrect results or device failure and that can directly affect patient safety. So building embedded software for medical devices is not like working on regular consumer gadgets. It comes with strict rules, higher quality expectations, and a strong focus on safety from the very beginning. Developers need to think not just about getting features to work, but also about long-term reliability, traceability, and compliance with medical standards.
This blog explores the key practices and decisions that go into building safe, reliable embedded software for medical products. From planning and testing to choosing the right platform and handling updates, each step plays a crucial role in creating devices that doctors and patients can trust.
Software Design Control Under IEC 62304
Medical software development is governed by a set of international standards and the most important among them is IEC 62304. This defines the life cycle requirements for the development of software that is intended to be used as part of a medical device. It outlines a framework that includes planning, requirements analysis, software architecture and design, implementation, testing, and maintenance. As we saw in earlier blogs, key concept introduced by IEC 62304 is the classification of software into risk categories: Class A for software with no safety risk, Class B for software that may result in non-serious injury, and Class C for software that could lead to serious injury or death. These classifications guide the depth of documentation, testing, and review required during development. Software design under this standard demands validation of processes and emphasizes traceability. Every requirement must be linked to its corresponding design, implementation, and verification artifact. This enables both effective quality control and the ability to demonstrate compliance during audits. Developers must ensure that documentation is continuously updated and that every change, no matter how small, is justified, tested, and approved. This degree of accuracy may seem challenging, but it is essential in ensuring patient safety and product reliability.
Unit Testing, Static Analysis, and Code Coverage
Functional correctness is a minimum expectation level in medical software. Beyond functionality, the software must also be robust under unexpected conditions and maintainable for years or decades after release. This is where unit testing, static analysis, and code coverage play an essential role in the development process.
Unit testing in embedded systems involves testing individual components or functions in isolation. It allows developers to validate logic and catch defects early in the development cycle. For this to work efficiently, the software architecture must be modular. Functions must be loosely coupled, and dependencies should be abstracted so they can be replaced by mocks or stubs during testing. Automated unit testing frameworks tailored for embedded systems help in writing repeatable and verifiable test cases.
Static analysis tools analyze the source code without executing it. These tools detect a wide range of issues from syntax errors and code smells to more critical problems like buffer overflows, race conditions, or violations of coding standards such as MISRA C. In case such kind of issues are left unchecked, it could pose serious safety risks in the field. Running static analysis as part of the regular development workflow ensures that the code is held to a consistently high standard.
Code coverage analysis ensures that the testing strategy is thorough. It measures how much of the codebase is actually exercised during testing. While 100% coverage may not always be achievable or necessary, developers must be able to explain why any code is not tested particularly in safety-critical areas. Tools that measure line, branch, and decision coverage provide insights into testing gaps and help improve overall test completeness.
RTOS vs. Linux: Making the Right Platform Choice
Selecting between a Real-Time Operating System (RTOS) and Embedded Linux is one of the most fundamental architectural decisions in medical device development. Each has strengths and trade-offs, and the decision must be driven by the device’s intended use, performance needs, and regulatory constraints.
An RTOS is typically preferred for devices that require high reliability, low latency, and deterministic response times. Systems such as FreeRTOS, Zephyr, or ThreadX provide lightweight scheduling, minimal overhead, and predictable timing behavior. These platforms are particularly well-suited for wearable or battery-powered devices that must operate for long periods on limited resources. RTOS-based systems are easier to verify and validate under IEC 62304 and often carry fewer certification burdens. For example, safeRTOS, Micrim OS, QNX pre-certified for safety standards like IEC 61508, ISO 26262, ISO 62304. So there is no need to qualify OS for certain standards.
Embedded Linux, by contrast, is chosen for its rich features, support for complex user interfaces, networking stacks, file systems, and multi-process capabilities. Devices such as imaging consoles, diagnostic terminals, and networked monitors often rely on Linux because of these capabilities. However, the use of Linux comes with its own set of challenges. Longer boot times, memory demands, and the need for kernel and driver management can complicate both development and certification. Real-time behavior also requires special kernel configurations or patches like PREEMPT-RT.
Selecting the wrong platform can lead to performance issues, security vulnerabilities, or even regulatory rejections. Therefore, a clear understanding of system requirements, lifecycle plans, and regulatory expectations must guide the decision between RTOS and Linux.
Watchdog Implementation and Fault Recovery Techniques
Bug or Failure is unavoidable in any system, but in medical devices, recovery must be swift, safe, and well-controlled. Watchdog timers are a fundamental tool used to detect system malfunctions such as software hangs or infinite loops. A properly implemented watchdog resets the system if it is not regularly "kicked" by the running software, thus indicating that something has gone wrong.
A layered approach to fault detection often involves both hardware and software watchdogs. The software layers monitor individual subsystems or tasks, while the hardware watchdog provides an independent safety net. This hierarchical approach enables early detection of localized issues and avoids unnecessary full system resets. For example, ECG Task is expected to update readings every 100 ms. If no update for 300 ms, the software triggers a task-level reset and logs a warning. SpO Task Continuously receives signals from the sensor. If it fails to report for 1 second, it attempts to reinitialize the sensor interface. UI Task Monitored for frame rendering within time constraints to detect UI freezes.
Beyond the watchdog, robust fault recovery mechanisms must be integrated into the software. This can include safe-mode boot, where the system loads a minimal version of the firmware with only essential features enabled. It can also include persistent logging of error conditions and resets, enabling engineers to trace and fix root causes. Redundancy in critical components, dual-bank firmware support, and real-time CRC checks on memory and data are some of the techniques that enhance the resilience of the system.
These methods are particularly important in Class C systems, where device failure could result in life-threatening consequences. Designing for fault tolerance and graceful degradation ensures that even in the worst-case scenarios, the system behaves safely.
Version Control and Change Management
Effective version control and change management are regulatory requirements. Traceability, reproducibility, and controlled change are core principles in ensuring that the device’s behavior is well understood, both during development and after deployment.
Modern version control systems like Git, when used with disciplined workflows, provide a strong foundation for software traceability. Every commit should correspond to a feature, requirement, or bug fix. Merging code into the mainline should follow structured review processes, and releases must be tagged with meaningful version numbers tied to configuration and documentation records.
Change management extends beyond source code to include configuration files, toolchain versions, test scripts, documentation and even hardware abstraction layers. Each change must go through an impact analysis that considers how the modification affects system behavior, safety risk, and test coverage. A formal review and approval process is essential before any change is integrated into a release.
Automation tools for continuous integration and deployment (CI/CD) are helpful in maintaining consistency and audit-readiness. Automated build and test pipelines can generate logs, test reports, and coverage data, which together form part of the product’s technical file during audits or regulatory submissions. This traceable, auditable, and automated approach to managing change is not just efficient, it’s a critical safeguard in ensuring device safety over its operational life.
Let’s see an example, Change in ECG Sampling Rate in a Patient Monitoring Device is requested by product owners. This seems like one line change, but it involves
- Configuration file change - Sampling rate parameter in a config .ini or .xml file must be changed
- Test scripts change - Automated unit and integration tests must be updated to check waveform correctness at 500 Hz
- Documentation - Design docs, user manuals, and software requirements specs must reflect the new sampling rate
- HAL/Driver change - The hardware abstraction layer managing ADC/DMA must ensure it supports the increased rate
- Impact analysis - Faster sampling may increase CPU load, possibly delaying other critical tasks like SpO₂ processing — introducing a new safety risk
Formal Review and Approval
- The change is logged in a change control system (e.g., Jira).
- A risk review (per ISO 14971) is triggered.
- A board including R&D, QA, Regulatory, and Clinical experts review the change.
- Only after sign-off, the change is merged into the release branch.
Conclusion
Developing embedded software for medical devices requires more than technical expertise, it demands a culture of quality, safety, and accountability. Developers must not only solve complex engineering problems but also meet stringent regulatory requirements that ensure patient well-being. By embracing IEC 62304 as a guiding framework, enforcing rigorous testing and code quality practices, choosing the right software platform based on system needs, designing fault-resilient architectures, and implementing robust version control and change management strategies, developers can build software that is both reliable and certifiable.
At Embien Technologies, we have been part of numerous medical device journeys, contributing embedded software to products that improve diagnosis and save lives. Our experience confirms that adopting the right engineering practices from the beginning is the most effective way to achieve compliance, minimize risks, and ensure long-term maintainability. As the healthcare industry continues to adopt digital solutions, embedded developers stand at the frontlines
