NeoGUARD
Health · App
An application that supports hospital staff in identifying complications during labour
Situation
In busy clinical settings, midwives and doctors often manage multiple births at once. Monitoring fetal health via CTG (Cardiotocography) is critical, but interpreting results manually is time-consuming, subjective, and prone to error. An AI-supported mobile app could enhance diagnostic accuracy and reduce cognitive load during high-stress situations.
Task
Design a user interface for an AI-powered MVP that can analyze CTG scans, guide clinical decisions in real time, and build trust through transparent feedback. All under tight time and resource constraints.
Action
I led the UX/UI design within a fast-paced design sprint.
User Research
Conducted user research and journey mapping to understand the midwife workflow in clinical environments.
Concept
Designed user flows and wireframes based on real-world pain points.
Design
Developed a minimalist interface for smartphones and tablets, with iconography and color coding chosen for quick recognition over recall.
Feedback loop
Built a feedback loop enabling users to rate scan results, strengthening model accuracy over time.
Built for a phone or a tablet at the bedside. A scan reads as one screen, one confidence percentage, and one suggested action, with nothing else competing for attention.
Result
NeoGUARD reads a CTG strip and flags the next clinical action within seconds. It's currently in clinical trials.





