CATEGORY:
University
GENRE:
Healthcare & First-Responders
DATE:
May 20, 2025
TECHNOLOGIES:
C#, Unity, Next.js, Vercel, PostgreSQL
EMT Vision
about.
EMT Vision is an AI- and AR-powered smart headset developed to assist emergency medical technicians (EMTs) and paramedics during field operations. The device integrates Microsoft HoloLens 2 hardware with Unity, Azure, and OpenAI APIs to provide real-time transcription, summarization, and display of patient data in the user's field of view.
The project's main goal is to enhance situational awareness, reduce cognitive load, and improve documentation accuracy for first responders in high-stress environments. EMT Vision automates the capture and analysis of patient–paramedic conversations, converts them into structured data, and overlays key information through an intuitive hands-free AR interface.
development.
EMT Vision was built using a research-driven, user-centered engineering approach. The project began with interviews and ride-along observations with Santa Clara City paramedics to understand real operational pain points. Existing tools like ImageTrend and manual ePCR documentation were functional but cognitively taxing during high-stress calls. These insights shaped every technical and design decision moving forward.
From there, the headset software was developed in Unity, permitting the easy integration and deployment of AR software. While this was primarily written in C#, a website frontend, created with hospital staff in mind, was created with Next.js and tied to our headset with a secure PostgreSQL database.
results.
EMT Vision was evaluated through a week-long series of simulated emergency scenarios designed to mirror real-world conditions. We tested the system’s ability to extract accurate patient information when multiple people were speaking, in high-noise environments, and when incorrect information was later corrected mid-recording. The headset consistently demonstrated reliable data capture and structured report generation under chaotic conditions. In recognition of its impact and technical execution, EMT Vision won 1st Place – Best Emergency & Medical Response Project at the SCU Senior Design Conference 2025.
