Stryker Medical
Recovery AI iOS App
IoT / Chatbot / Mobile App
Role
UX Research
UI Design
Work
Native iOS UI design
Chatbot avatar interactions
IoT process and flow design
Functional UI build
Phase 2 approach
Key Product Takeaways
Native iOS app ensures performance and compatibility
Natural language processing for more simpler AI appointment interactions
Personalized tracking of recovery milestones
IoT-enabled wearable integration
Aggregates long-term recovery patterns and insights for health providers
Product Summary
The Problem
Stroke recovery outcomes need improvement through more guided, hands-on support
Communication gaps contribute to unnecessary return visits
Patients lack clarity on how their recovery is progressing
UX Considerations
Ensure accessibility for users recovering speech, motor skills, or memory function
Deliver accurate, real-time health data capable of signaling a potential health crisis
Design a simple and supportive onboarding process for patients and caregivers
Outcomes
Fewer return visits due to more informed and engaged recovery processes
Improved patient understanding and adherence to recovery plans
Increased confidence through visible progress and consistent feedback
Ways we learned
Generative / Evaluative
1:1 interviews
Sit withs
Heuristic/WCAG analysis
Competitive analysis
Group Feedback
Design workshops
Prototype demos
Polling
1:1 testing
Focus groups
Synthesis
Personas
Flow mapping
Pain point mapping
Prioritized user wants / needs
Design System
Created a preliminary design system to support early-stage prototyping, ensuring consistency across components while allowing for rapid iteration. This system established foundational styles, reusable elements, and scalable patterns to streamline design decisions and accelerate product development.
Flow Mapping
Though many user flows, interaction approaches, and overall layouts were explored, these wires represent the direction final designs ultimately followed.