Prenac assistant
AI-powered elderly care companion for enhanced support and safety
The challenge: A healthcare startup approached me to design an AI companion for the elderly. The goal? Create a friendly bot that could chat, entertain, and provide crucial medical support for seniors living independently.
My role: As one of two UX/UI designers in a six-person team, I worked closely with developers, product owners, and our project manager. Our goal was to improve elderly care by creating thoughtful, technology-based solutions that could make a real difference in seniors' lives.
What I brought to the table:
- Deep dive into the world of our elderly users through hands-on research
- Crafted interfaces that even the most tech-shy seniors could navigate with ease
- Mapped out user journeys for critical features like med reminders and fall alerts
- Breathed life into the AI bot's interface with detailed wireframes and polished prototypes
- Worked hand-in-hand with our tech wizards to seamlessly integrate AI magic
- Continuously refined designs based on real user feedback and team insights
Discovery & Research Phase
Our approach focused heavily on an in-depth discovery phase to ensure we addressed the core needs and challenges of elderly users.
Analysis of Academic Studies: We conducted a comprehensive review of studies related to elderly care, focusing on fall prevention, pain management, and cognitive engagement. This helped us gain a deep understanding of the problem landscape.
Problem Categorization: Based on the insights from the studies, we categorized the key challenges into major themes to identify possible solution pathways.
Market Research: We explored existing solutions in the market to gather additional insights, uncover gaps, and identify best practices.
Insight Synthesis & Thematic Categorization: We organized the gathered insights into three core themes, each with a potential solution approach.
User Persona Development: We identified four distinct user personas, focusing on diverse needs and pain points.
Journey Mapping: We mapped detailed journeys for each persona, highlighting valuable AI bot interactions.
Concept Development & Information Architecture
Site Map: We developed a comprehensive site map to outline potential functionalities. This helped us assess complexity, time investment, and business value.
Feature Prioritization with Card sorting: To align the team on the MVP scope, we applied the Card Sorting Method ensuring clarity on priority features and test how external users understand and categorize the ideas.
Design & Prototyping
Simple sketches to detailed designs: we started with basic outlines of our ideas, then moved on to more detailed versions. This step-by-step approach helped us:
- Show how users would move through the app
- Test different ways people might use it
- Make sure everything worked well together
- Get feedback early to improve our designs
- Create a clear picture of what the final product would look like
- Spot and fix any issues before building the actual app
Easy-to-Use Design: We made sure our app works well for everyone, especially older adults. We used special tools to check things like color, text size, and spacing. This helps make sure all users can see and use the app easily, no matter their age or abilities.
Key Results
- User-Focused Design: Created a solution that meets elderly users' specific needs.
- Clear Product Vision: Picked the most valuable features for our first version.
- Easy to Use: Made sure everyone can use the product, regardless of ability.
- Team Teamwork: Brought together user needs and tech possibilities in a diverse team.
This project shows how I can lead research, understand complex ideas, and turn them into good designs. I'm excited to talk more about how these skills can help with new projects at Schneider Electric.