Every minute matters during a stroke.
For ischemic stroke patients, delays in treatment significantly increase the likelihood of long-term disability or death. Yet emergency medical technicians (EMTs) are often required to make critical decisions with limited information in fast-paced, high-pressure environments.
In partnership with researchers at UCSD Cognovate Labs, our team explored how emerging EEG technology could support Emergency Medical Services (EMS) in identifying stroke patients earlier and connecting them to appropriate treatment faster.
As a Product Designer and Design Consultant, I worked alongside neuroscientists and fellow designers to translate complex medical research into an intuitive digital experience for first responders.
- 4th
Leading cause of death
in the United States.
- 1.9M
Neurons lost per minute
of untreated stroke.
- ~22%
Strokes missed
or misdiagnosed by EMS in the field.
Stroke diagnosis in the field depends on what EMTs can see.
EMTs commonly use the BEFAST assessment (Balance, Eyes, Face, Arms, Speech, Time) to identify potential stroke symptoms. While effective, BEFAST relies on observable behaviors — which can sometimes be misleading.
Stroke-like symptoms can be caused by other conditions, and some stroke patients may not present obvious symptoms at all. Without objective neurological data or comprehensive patient history, EMTs face real uncertainty determining whether a patient is truly experiencing a stroke.
Balance · Eyes · Face
Loss of coordination, vision changes, drooping.
Arms · Speech
Weakness on one side, slurred words.
Time
Note the moment symptoms began — every minute counts.
“How might we help EMTs make faster, more confident stroke assessments in the field — without adding complexity to an already stressful workflow?”
Three themes reframed the design.
Through interviews with practicing EMTs and conversations with people affected by stroke, three findings kept resurfacing:
- BEFAST builds confidence but doesn't guarantee it. EMTs rely heavily on behavioral assessments, but symptoms can be ambiguous and they don't always feel confident in their conclusions.
- Context matters as much as symptoms. Understanding a patient's medical history often changes how a behavior is interpreted. A symptom that looks stroke-related may actually be a pre-existing condition.
- Every minute of delay compounds downstream. Hospitals often receive incomplete information before patient arrival, leaving care teams less time to prepare treatment resources.
“The problem wasn't simply identifying strokes — it was helping EMS teams make informed decisions with greater confidence and communicate critical information earlier.”
Four principles for designing under pressure.
Increase diagnostic confidence
Provide objective data alongside behavioral assessments.
Reduce cognitive load
Present complex EEG information in a way non-specialists can quickly understand.
Support existing workflows
Integrate with BEFAST rather than replacing it.
Enable faster hospital prep
Share critical patient information before arrival.
An EMS-facing app built into the BEFAST workflow.
NeuroALERT pairs four design decisions — each grounded in what we heard from EMTs — to reduce uncertainty without adding cognitive load.
Built into the protocol, not around it.
EMTs can document observed symptoms using a workflow that mirrors their existing BEFAST process.
Research showed that adoption would be more likely if the solution aligned with current EMS practices rather than introducing a completely new process.
Neurological activity, made readable.
Instead of displaying raw EEG outputs, NeuroALERT translates neurological activity into understandable indicators and abnormality summaries.
Interviewed EMTs raised concerns about interpreting highly technical EEG data while managing patient care — so the visualization had to do the translation for them.
Hands-free history, captured in real time.
The application records and transcribes patient history through voice input.
EMTs often have limited time and attention. Voice capture reduces manual entry while preserving valuable context.
Route to the right facility, ahead of arrival.
NeuroALERT recommends nearby stroke-capable facilities and lets EMTs send patient information before arrival.
Earlier communication helps hospitals prepare treatment teams and reduce handoff delays.
Validation from the people who'd use it.
We validated the concept through iterative feedback with one of our EMT participants. The integration of patient history, EEG insights, and the BEFAST workflow could increase confidence during field assessments while minimizing additional cognitive burden.
Brought to a pilot, the potential impact extends to:
Faster stroke identification
Objective data alongside behavioral cues.
Diagnostic confidence
Less guesswork under pressure.
Earlier hospital prep
Treatment teams ready on arrival.
Stroke-to-treatment time
Minutes saved, neurons preserved.
Designing for high-stakes environments changed how I think about clarity.
Before this project, stroke care felt like an abstract medical problem. Working alongside neuroscientists, EMTs, and individuals directly affected by stroke turned it into a deeply human challenge.
Unlike consumer products, healthcare tools must balance clarity, speed, accuracy, and trust simultaneously. Designing the interface was only part of the challenge — the real work was understanding what information mattered most and how to surface it at the right moment.
What I'm carrying forward.
Research as a north star
Letting user insights drive product decisions from concept to solution.
Cross-disciplinary collaboration
Translating between neuroscience, medicine, and design.
Design under pressure
Balancing clarity, speed, accuracy, and trust simultaneously.
Information triage
Knowing what to surface, and when.