Aisra – Personalized Injury Rehab App for Athletes Inspiration: Athletes, especially basketball players, often face injuries that can be costly and time-consuming to recover from. Accessing sports therapists isn't always feasible due to high costs, time constraints, or mobility issues. We built Aisra to provide a convenient, affordable, and tech-forward alternative that helps athletes rehabilitate with personalized guidance right from their phones.
What It Does: Aisra is a mobile app that helps injured athletes recover and strengthen by offering: Custom workout plans based on their specific injuries. Progress tracking through motion detection and analytics. Gamified recovery with rewards and milestones. AI-powered suggestions for exercises and care. Future features: connecting users with top sports therapists and rehab specialists.
How We Built It: User Research & Pain Points: We began by researching injury trends among basketball players and understanding their recovery struggles. Prototyping: Designed UI/UX in Figma and built a prototype with React Native and Expo Go. Motion Tracking: Integrated Sency Motion SDK and VisionCamera to track reps, form, and injury-prone movement. AI Integration: Used LLMs like Claude Sonnet, Tempo.ai, and Together.ai for personalized recommendations. Payments & Rewards: Incorporated OpenNode, Stripe, and Taproot for future Bitcoin-based incentives. Back-end & Testing: Used Xcode and Swift for native performance testing; development and debugging were done with VS Code, npm, and CocoaPods.
Challenges We Ran Into: SDK Integration: Integrating native Swift SDK (SMKitUI) with React Native posed major compatibility issues, especially with module resolution in Xcode. Expo Limitations: Expo lacked support for the native frame processing we needed, requiring a full rebuild in bare React Native. Cross-Timezone Collaboration: Our global team had to navigate communication and scheduling across different countries. Partner & SaaS Evaluation: Identifying reliable third-party tools took time due to extensive trial, error, and meetings.
Accomplishments That We're Proud Of: Successfully integrated motion tracking using the phone’s camera for personalized rehab exercises. Learned and implemented Bitcoin payment via legacy and lightning address integration using OpenNode. Collaborated globally with engineers, designers, and AI researchers. Completed accelerator programs and formed connections with mission-aligned innovators.
What We Learned: Communication is key when building across time zones and disciplines. Documentation matters – poor SDK docs slowed us down significantly. Learned advanced technical workflows like LLM fine-tuning, Bitcoin ecosystem development, and Swift-React Native bridging. Gained hands-on experience troubleshooting cross-platform motion SDKs.
What’s Next for Aisra Inc: Beta Testing: 100 Real basketball players will test the full version for feedback and iteration. Partnerships: Collaborating with sports therapists, athletic clubs, and training academies. Tech Expansion: Improve AI-driven recovery, integrate deeper with Bitcoin rewards, and resolve Swift-React Native barriers. Scalability: Expand into other sports, injury types, and eventually into preventive care and performance enhancement.
Built With: Languages: JavaScript, Python Frameworks: React Native, Swift SDKs/APIs: Sency Motion SDK, VisionCamera, SMKitUI, OpenNode, Stripe, Tempo.ai, Claude 3.7 Sonnet, together.ai Design: Figma Tools: VS Code, npm, Xcode, Excel, Google Sheets, Bolt.new Platforms: iOS (tested via Xcode), Bare React Native (non-Expo) Cloud: Firebase (planned), Taproot integration via Lightning node
Team: Jesselynn Contreras – Founder, Engineer, Strategy, Payment System Alex Yu – Co-founder, Product & Partnerships Aaryan Bhardwaj – Engineer, AI Model & Rehab Logic CryptoScholars – Prompt Engineer, Project Manager, Tokenomics Chloe Pham – Developer, Motion Tracking & Native Integration
Doctors Dashboard authorization/sign up is test@gmail.com 12345678-password
To test Stripe, use the following test card numbers based on the card brand you want to simulate a successful payment with.
Use this 5555555555554444
Built With
- bare-react-native-(non-expo)-cloud:-firebase-(planned)
- bitcoin
- bolt.new-platforms:-ios-(tested-via-xcode)
- claude-3.7-sonnet
- excel
- google-sheets
- integration
- languages:-javascript
- lightning
- npm
- opennode
- python-frameworks:-react-native
- smkitui
- stripe
- swift-sdks/apis:-sency-motion-sdk
- taproot
- tempo.ai
- together.ai-design:-figma-tools:-vs-code
- tokenomics
- visioncamera
- xcode
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