How Wireless Coexistence Testing Exposes Real‑World Medical Device Behavior

Modern medical devices rely on wireless connectivity to support alarms, clinician workflows, and continuous patient monitoring. Some wireless performance issues appear intermittently and only under specific interference conditions. These behaviors can be hard to reproduce late in development or after deployment. Coexistence testing provides a structured way to reveal and understand these failure modes before they become field issues.

For connected medical devices, it is a practical way to reduce patient risk and support regulatory readiness by demonstrating how a device performs in the presence of real‑world interference. Regulatory guidance points manufacturers to ANSI C63.27 as a recognized framework for evaluating wireless coexistence, and the medical device community often references AAMI TIR69 to frame coexistence evaluation within an overall risk management process.

Yet many R&D engineers face the same challenge: how to turn coexistence testing into clear, repeatable evidence they can use throughout development—and later, in a submission narrative—without being overwhelmed with custom setups and one‑off tests.

Start with the question that matters: What must never fail?

Wireless coexistence testing becomes far more effective when it starts with an outcome‑driven question:

What function must never fail when wireless performance is disrupted by interference?

For medical devices, this often maps directly to essential performance or clinical workflow:

• Do alarms arrive within an acceptable time window?
• Does therapy delivery remain continuous and predictable?
• Does patient data remain timely and usable under interference?

Defining this outcome first keeps coexistence testing grounded in clinical reality. The goal is not to optimize RF conditions. The goal is to show that the device continues to perform its intended function under defined interference scenarios.

From there, teams can define what acceptable performance looks like and select measurements that reflect that behavior. In practice, the most useful key performance indicators (KPIs) are often application‑level or system‑level—such as latency, throughput stability, jitter, or packet reliability—because they directly indicate whether alarms arrive on time, data streams remain continuous, and control loops behave as intended.

Use ANSI C63.27 tiers to scale complexity without losing control

ANSI C63.27 defines three tiers of coexistence evaluation with increasing interference complexity.

Based on the risk associated with a function failing due to wireless interference, teams can determine which tier their device should be evaluated against. Although not a regulatory requirement, it is considered best practice to test under conditions that closely reflect real‑world environments in order to better understand a device’s wireless performance.

At a high level, the tiers are selected based on the severity of consequences if wireless performance were to fail:

• Tier 3 (least severe consequences): Establishes baseline behavior. Testing is performed with minimal interference, and only a limited amount of testing is required.
• Tier 2 (moderate consequences): Introduces greater interference severity. Additional unintended signals are applied, typically evaluating adjacent‑channel or co‑channel interference scenarios.
• Tier 1 (unacceptable or potentially life‑threatening consequences): Requires the most rigorous evaluation. Dense, multi‑signal interference scenarios are applied to emulate challenging environments such as active hospital settings or highly congested wireless environments (for example, concerts or stadiums).

Across all tiers, repeatability matters. If results vary depending on setup details or who ran the test, it becomes difficult to compare outcomes or defend conclusions.

The repeatability problem—and why it slows engineering teams down

Many medical device teams know what they want to test, but lab reality gets in the way:

• Excessive manual setup and re‑setup
• Too many adjustable variables (frequency, power, timing, bandwidth)
• Too many ways to unintentionally change a test condition

As a result, coexistence evaluation often becomes a late‑stage fire drill—when schedules are tight and design changes are expensive. Iterative testing through external test houses can further extend development cycles, delaying market entry and increasing overall program cost. Inconsistent setups also make it harder to build an evidence trail that can be reused in design reviews or regulatory discussions.

A repeatable approach—using structured scenarios, controlled power delivery at the equipment under test (EUT), and consistent result capture—helps teams move coexistence testing earlier and use it as a decision‑making tool rather than a last‑minute hurdle.

What to look for in a coexistence test platform for medical devices

A practical coexistence test platform needs three fundamentals: realistic interference, control of what the EUT experiences, and results engineers can reuse.

Realistic interference scenarios: Medical environments rarely involve a single interferer. The ability to generate multiple interference types—such as adjacent, co‑channel, or harmonic—and combine them into dense scenarios helps better represent real operating conditions.

Power delivered where it matters: Uncertainty about the power level at the EUT is a common lab challenge. Automated calculation and control of delivered signal and interference power—maintaining a defined signal‑to‑interference ratio at the receiver—reduces ambiguity and improves confidence.

Sequenced automation for consistency: Automation helps standardize waveform selection, frequency and power settings, timing, and recovery behavior, reducing manual variation and freeing engineers to focus on analysis.

Standards‑aligned starting points: Predefined test scenarios aligned with ANSI C63.27 provides a structured foundation. Teams can run meaningful coverage early and extend scenarios as risk becomes clearer.

Results you can attach to decisions: Results should be easy to review, compare, and reuse—supporting trend analysis across power levels, interference types, and mitigation strategies, while helping build traceable documentation.

Apply AAMI TIR69 thinking: Test to reduce risk

AAMI TIR69 frames wireless coexistence evaluation as part of risk management. In practice, this means:

• Identifying clinical use cases tied to safety or essential performance
• Selecting KPIs that reflect those use cases
• Scaling test scenarios using ANSI C63.27 tiers
• Recording outcomes consistently so results can be traced and explained

When applied early, this approach reduces rework and creates evidence that supports both engineering decisions and regulatory conversations.

Start with evidence, not assumptions

Wireless coexistence testing for medical devices is ultimately about confidence—confidence that devices behave as intended in real environments, and confidence that performance claims are supported by repeatable evidence.

By focusing on what must never fail, scaling complexity thoughtfully, and prioritizing repeatability, teams can move beyond guesswork and use coexistence testing as a practical engineering and risk‑reduction tool.

To explore full capability and specification details, download the Keysight Wireless Coexistence Test Solution Data Sheet.