EN
Some requests in a funding application get waved through with little pushback. Equipment usually isn’t one of them.
Whether you’re applying through a major program like Horizon Europe, NIH, or NSF, or through a national or institutional call, research-grade tools come with a price tag reviewers want to see justified.
And when the request is for something as specialized as an eye tracking system, they tend to read even closer.
Let’s walk through what reviewers are actually looking for and how to make your request hold up under scrutiny.
In most proposals, reviewers don’t spend much time on the paper stock or participant snacks. But they do pause at the equipment.
Research funding is competitive, and equipment funding even more so.
So when reviewers come across a line item for specialized tools like eye tracking systems, they’re looking for fit. Does this match the study design? Will it support reliable, reproducible results? Is there a plan for how it will be used, accessed, and maintained?
Clear justification signals a well-thought-out project. Vague or generic reasoning does the opposite and can make reviewers question whether the rest of the proposal holds up.
A Clear Narrative That Matches Your Aims
In most major funding systems, reviewers are evaluating how well your requested resources support your research goals, not just whether you’ve followed the budget format.
• Horizon Europe encourages applicants to describe personnel, consumables, and equipment in narrative form, especially under lump-sum grant structures like ERC Proof of Concept.
• NSF proposals include a Facilities, Equipment & Other Resources section that’s reviewed as part of both Intellectual Merit and Broader Impacts.
• At NIH, equipment over $5,000 must be individually justified as essential to the specific aims, particularly if similar tools aren’t already available at the institution.
What this means for your proposal: Make it clear how the system connects to your study. What specific task does it enable? Why is that task central to your research design? If the connection between aim and equipment isn’t obvious, reviewers are more likely to question the request.
Institutional Fit and Long-Term Planning
Funders also look at how equipment will be managed over time. They want to see that the tool is well-matched to the environment — and that it won’t sit unused or unsupported once the grant is awarded.
• NIH encourages applicants to detail how equipment will be maintained and shared, and how it avoids unnecessary duplication.
• NSF asks researchers to describe how new tools complement existing facilities and how they’ll be integrated into long-term lab use.
What this means for your proposal: Be ready to show how the system will be used beyond setup. That includes where it will be housed, who will manage it, and how it fits with your institution’s existing resources.
Eye tracking systems often show up in proposals for HMI, neuroscience, or simulator-based research. But even when the system is well-chosen, the justification can fall flat.
Here are a few patterns that tend to raise questions for reviewers:
• Generic descriptions, like “eye tracker with high resolution,” without connecting specific features to the study design
• Vague reasoning, such as “we need it for participant behavior,” without clarifying what’s being measured or why precision matters
• Overlooking data quality risks, including calibration issues, loss of tracking, or system mismatch with the research environment
• Assuming access, for example referencing a tool the lab already owns without explaining its limitations or availability
• Substituting quantity for quality, such as requesting multiple lower-tier systems instead of making a case for one high-performance setup
Even if the rest of the proposal is strong, these gaps in reasoning can make it harder for reviewers to endorse the equipment request – or trust that it’s essential to the work.
A good equipment justification doesn’t need to be long, but it does need to be clear. The goal is to show reviewers that you’ve chosen the right tool for the job, and that you know what it takes to get reliable data from it.
Here’s what that looks like in practice:
Match the System to the Task
Explain what the system needs to do and why that task matters. Are you measuring rapid attention shifts in a driving simulator? Tracking gaze across multiple screens in a control room? Reviewing head-stabilized data from participants with glasses or diverse facial features? Let the study design lead the argument.
Emphasize Data Quality and Reproducibility
Reviewers want to know the data you collect will stand up for analysis. If the system helps reduce noise, minimize dropout, or avoid re–calibration mid-session, that’s worth stating clearly.
Frame It as a Diverse Research Asset
If the system will be used across multiple studies, shared across teams, or adapted for different participant groups, mention it. Many reviewers value equipment that supports not just your study, but the broader research environment.
Address Alternatives Without Over-explaining
It’s okay to acknowledge that lower-cost options exist, as long as you explain why they wouldn’t work for your setup. Keep the focus on your project’s needs, not a feature-by-feature comparison.
When justifying equipment, researchers often use language that clearly links the system to the research task and environment. Here are a few examples of phrasing that reflects that approach:
“The proposed eye tracking system is essential for Aim 2, which involves measuring millisecond-level attention shifts in a dynamic driving simulator. Alternative tools do not offer the required sampling frequency or stability under vibration.”
“This system will be procured within the first 12 months and housed at [Institution’s Human Factors Lab], where it will be available for the duration of the project and future research using the same infrastructure.”
“Although the lab currently has access to a portable eye tracker, it is not suitable for this cockpit-based study due to screen layout complexity, required viewing angles, and lack of multi-camera support.”
These examples shouldn’t be treated as templates, but the pattern is helpful: research aim → system requirement → practical context. Reviewers want to see that connection.
If you’re planning to include eye tracking in a funding request, timing matters just as much as wording.
• Horizon Europe and national research councils often release major calls between late summer and early fall. If your application is due in Q4, you’ll want to start framing your equipment justification in August or September.
• NSF and NIH typically set deadlines between January and April, with program-specific cycles that may require earlier prep.
• Internal university grants vary, but many align with semester planning. Expect application windows in March–May and again in September–October.
If you’re not applying immediately, it’s still worth preparing a clear justification in advance. Many researchers reuse the same equipment rationale across multiple applications, adapting it to match each funder’s structure and terminology.
Reviewers usually don’t need a deep technical breakdown. They just need to understand what the system is for, why it matters to your research, and how it fits into the bigger picture. If that part’s clear, the rest is much easier to get behind — and worth double-checking before you hit send.
If you need system specifications or setup details to support your justification, feel free to get in touch with us.
