Embedded Software for Medical Devices: Building Safe, Compliant, Reliable Firmware
Embedded software for medical devices is the code inside the products patients and clinicians depend on: patient monitors, infusion pumps, imaging consoles, wearables, implants, and surgical tools. It reads sensors, drives actuators, runs control loops, manages connectivity, and keeps a device behaving correctly — often for years, often with a life on the line.
It is also one of the most demanding areas of embedded engineering: the software has to be correct, deterministic, and documented — and the team that builds it has to be able to prove all three.
What embedded software in a medical device actually does
A medical device’s embedded software sits between the hardware and the clinical function. At the lowest level it handles drivers and board bring-up: sensors, ADCs, radios, displays, and power management. Above that sit the real-time tasks, and above those the application logic, user interface, connectivity, and update mechanism.
The mix depends on the device, from a wearable on a small RTOS to an imaging console on Embedded Linux.
What these devices share is that the software is part of the product’s safety case.
Why it matters: safety, determinism, and long life
Three properties dominate medical-device software. First, safety. Software failures can injure a patient, so the design has to anticipate failure modes: a sensor reading out of range, a task overrunning its deadline, memory corrupting, power dipping. Defensive design — watchdogs, sanity checks, safe states — is not optional decoration. It is the product.
Second, determinism. Many medical functions are real-time: a control loop must run on schedule, an alarm must fire within a bounded time, a sample must not be dropped. The design has to guarantee timing under worst-case conditions, not average ones.
Third, long life. Medical devices stay in the field for a decade or more, so the software has to be maintainable: supported operating systems, reproducible builds, a secure update path, and documentation an engineer who was not on the original team can still follow.
The regulatory landscape
Medical-device software is regulated, and the regulatory picture is the frame every project works inside. The details below are general industry knowledge, not legal advice — the exact requirements depend on the device class, the market, and the manufacturer’s quality system.
In the United States, the Food and Drug Administration (FDA) regulates medical device software, including software as a medical device (SaMD) and software that is part of a device. Software is classified by risk, and the documentation and validation expected scale with that risk. A manufacturer must show the software was developed under a controlled process, with requirements traceable through design, verification, and validation.
IEC 62304 is the international standard for the medical device software lifecycle, covering development, risk management, configuration management, and problem resolution. It ties the rigour of each process to the software safety class — A, B, or C, depending on the harm a software failure could cause. Class C, the highest, demands the most: detailed design documentation, unit-level verification, and full traceability. Classifying early matters: without it, the standard defaults the whole system to the highest class.
ISO 13485 is the quality management standard for medical devices, covering design controls, document control, supplier management, and corrective action, with the software process sitting inside it. In the European Union, the Medical Device Regulation (EU MDR) governs market access and treats software explicitly: embedded software falls under the same class as the product it controls, and software with an independent medical purpose is classified in its own right.
Cybersecurity is now a first-class regulatory concern. The FDA’s final guidance on cybersecurity in medical devices expects manufacturers to describe the software components in their products — including third-party software such as the operating system — in a software bill of materials (SBOM), and to explain how security updates will be delivered over the device’s life. Secure boot, signed updates, and a plan for vulnerability management are part of the product, not an afterthought.
Real-time and safety requirements in practice
Architecture comes first. Separating the safety-critical path from the rest of the system — for example, running the control loop on a dedicated core or a separate microcontroller, with the user interface and connectivity isolated from it — makes the safety case simpler and the system easier to reason about.
Timing has to be designed, not hoped for. That means choosing scheduling and communication mechanisms with known worst-case behaviour, measuring actual execution times, and testing under load.
Failure handling has to be explicit. Every sensor input, every communication link, every allocation has a failure mode, and the design should say what the software does in each one: hold the last good value, enter a safe state, raise an alarm, log the event. “It should never happen” is not a failure-handling strategy.
Testing has to be systematic: unit tests for components, integration tests for interfaces, and system tests against the requirements — with traceability tying each test back to a requirement and a risk. The goal is not a test count; it is evidence that the software does what the requirements say, including when things go wrong.
Choosing a platform
The choice of operating system is one of the earliest decisions, and it constrains everything after it. Embedded Linux — often built with Yocto — fits devices with a user interface, networking, and significant application software: imaging consoles, patient monitors, gateways. It brings a full networking stack, a large ecosystem, and long-term support options, but it needs careful configuration to keep real-time behaviour predictable.
FreeRTOS fits small, low-power devices: wearables, disposables, simple sensors. Zephyr is a modern RTOS for connected devices needing Bluetooth or Wi-Fi alongside real-time control. QNX fits devices where isolation matters most — surgical robotics and complex imaging — where a fault in one component must not take down the rest.
The platform decision should be made against the device’s safety classification, its lifetime, and its connectivity — not against familiarity alone. A platform that is easy to start with but cannot be supported for ten years, or cannot demonstrate the timing guarantees the device needs, is the wrong platform.
The development lifecycle and validation
A medical-device software project runs on a lifecycle familiar to any embedded engineer — requirements, design, implementation, verification, validation — but with two differences: traceability and evidence.
Traceability means every requirement can be followed forward to design, code, and test, and backward from a test result to the requirement it verifies. When a requirement changes, the team can see exactly what else is affected. When a defect is found, the team can see which requirements and risks it touches. This is the mechanism that lets a team answer “how do we know this is safe?” with something better than an opinion.
Evidence means the process produces records: requirements documents, design descriptions, test protocols and results, risk analyses, review records. These are not paperwork for its own sake. They are the material a regulator, an auditor, or a customer reviews to judge whether the software was built properly. Documentation treated as part of the engineering work stays useful — including to the team’s future self, when the product needs a change years later. Validation — testing the finished device against its intended use — belongs to the product, but the software team’s contribution is the verification evidence: tests showing each requirement is met, and a risk analysis showing the residual risks are acceptable.
How HanahTech approaches this work
HanahTech LLC, founded in 2013 and based in North Wales, Pennsylvania, builds embedded systems, firmware, Yocto Linux, PCB designs, IoT, cloud, and mobile applications — from silicon to cloud. Medical devices are part of that work. Our team has built embedded software for medical products including a health gateway, a neurostimulation device, and a knee-movement monitoring device, working for clients who keep their names confidential, as we do for all of our customers.
Our approach to a medical-device project starts with the safety case, not the code. Before choosing a platform or writing a line of firmware, we work through what the device has to do, what can go wrong, and what evidence the product will need. That shapes the architecture — where the safety-critical path lives, how it is isolated, how timing is guaranteed — and it shapes the development process, so that traceability and testing are built in rather than added on.
We bring the same depth to the platform layer: Yocto Linux builds with reproducible images and a secure update path, RTOS-based firmware with deterministic scheduling, and board design and PCB layout when hardware and software are developed together. And because our work spans embedded, IoT, cloud, and mobile, we can build the whole product — device, gateway, cloud service, and app — as one system.
Building a medical device and need a team that understands both the firmware and the process around it? Get in touch. We would rather talk about your device’s safety case and your timeline than about our credentials.
Note: this article describes the regulatory landscape as general industry knowledge. It is not legal or regulatory advice, and the exact requirements for a device depend on its classification, its market, and the manufacturer’s quality system.
