ReliefLog

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Inspiration

Jesson worked in interventional pain management clinics where he saw firsthand how chronic joint pain affects patients’ daily lives and how physicians often struggle to get the full picture during short visits. While conducting research at Nicklaus Children’s Spine Institute, he also observed cases where seemingly minor conditions, like early spondylosis in young athletes, progressed into serious issues that forced them to quit sports prematurely. These experiences inspired the creation of ReliefLog — a tool designed to help patients recognize, manage, and communicate their pain more effectively while giving physicians the complete context they need to provide better, more informed care

What it does

ReliefLog is a GPT powered mobile app that helps users track, prevent, and manage joint pain. It allows users to log pain levels, stiffness, and mobility, then provides personalized, evidence-based advice on what activities to avoid, when to rest, and when to seek medical attention. For physicians, it compiles daily symptom logs into clear, exportable summaries, offering a complete picture of the patient’s pain trends and patterns.

How we built it

Framework: React Native with Expo Language: TypeScript State Management: Zustand with AsyncStorage persistence Navigation: React Navigation v7 Styling: NativeWind (Tailwind CSS for React Native) AI Integration: OpenAI

Challenges we ran into

One of the main challenges we faced was setting up the correct APIs. Implementing tools such as Google Maps and OpenAI required in-depth documentation review and research to ensure proper integration. Another challenge was scope creep — while we initially planned to include additional features like speech-to-text, we ultimately decided it wasn’t feasible within our project timeline.

Accomplishments that we're proud of

A major accomplishment we’re proud of is building a fully functional mobile app. Only one team member had prior experience with React Native and TypeScript, so we relied heavily on tutorials, YouTube videos, and AI assistance to learn quickly. Additionally, Jesson’s background in Biology brought valuable perspective to our team — helping us better understand the user’s pain points from a real-world standpoint. We’re also proud of conducting a comprehensive market analysis, which involved examining market data, financials, and target customer segments. This was an entirely new experience for us, as none of us came from a finance or business background.

What we learned

Through this project, we learned the importance of designing technology that’s both user-friendly and clinically responsible. We discovered how valuable continuous data can be for improving patient outcomes and how empathy-driven AI can make healthcare more accessible.

What's next for ReliefLog

Next, ReliefLog will focus on expanding its capabilities and accessibility. The development team plans to integrate additional AI models to improve the accuracy and personalization of pain analysis while deploying the app to the App Store and cloud platforms for scalability. A dynamic database such as Firebase will be connected to securely store user data, images, and AI-generated insights. Accessibility will be enhanced through text-to-speech features using tools like ElevenLabs, making the app easier for older adults to use. Finally, telehealth integration will be added, allowing users to connect directly with healthcare providers through secure video chat for more comprehensive, real-time care

Built With

• open-ai-api
• react-native
• tailwindcss
• typescript