Project Info
Inspiration
We were inspired by conversations with our grandparents and other elderly individuals who often spoke about loneliness, lack of purpose, and cognitive decline as some of the hardest challenges of aging. We wanted to build a compassionate, easy-to-use solution that helps them not only track their cognitive and emotional health, but also reconnect with loved ones and peers in a meaningful way. Our Product Our app provides an interactive dashboard where elderly users can track their progress across both mental health and cognitive function using short, engaging games and reflection activities. Key Features Daily Brain & Mood Games: Exercises inspired by the Stroop Test and List Recall games to assess attention, memory, and reaction speed. Progress Tracking Dashboard: Visual summaries that show improvement trends over time. Connection Mode: A “social circle” feature that lets users share results and messages with family or friends. Multiplayer Games with LLM Facilitation: Games can be played cooperatively or competitively, with a language model acting as a mediator or host, making the experience conversational and friendly. Accessibility for the Visually Impaired: Integrated Fish Audio APIs convert tasks and feedback into speech so users with limited vision can participate equally. How We Built It We developed the app using the MERN stack: Frontend: React Native for cross-platform mobile accessibility (iOS and Android). Backend: Node.js and Express for API handling and real-time communication. Database: MongoDB for secure, scalable storage of user data and performance metrics. Audio Layer: Fish Audio API for speech-based interactions and accessibility. Chat + Multiplayer: JanitorAI API for enabling conversational game facilitation and social connection. We also incorporated a token-based authentication system (JWT) for secure user sessions and integrated LLM-driven prompts that adapt the difficulty of tasks based on performance trends. Challenges We Faced Accessibility Design: Ensuring games were equally usable by both sighted and visually impaired users required extensive experimentation with audio feedback and timing. LLM Integration: Calibrating the language model to act as a friendly “game host” without over-responding or confusing users was a significant UX challenge. Data Visualization: Representing cognitive data trends in a way that is intuitive and not overwhelming for older users took several design iterations. What We Learned We learned how technology can bridge generational gaps when designed with empathy and accessibility in mind. We also deepened our understanding of integrating audio-based AI models, handling real-time multiplayer state management, and designing for users who are often overlooked by mainstream tech. Future Vision We plan to expand the app with: Personalized difficulty calibration using reinforcement learning and adaptive learning features. Integration with wearables (e.g., Apple Watch, Fitbit) to combine physical and cognitive metrics. AI-driven health insights for early detection of cognitive decline.
🧠 ElderCare Cognitive & Connection Platform
An empathetic, accessible app designed to help elderly individuals track cognitive health, combat loneliness, and reconnect with loved ones through engaging activities and social features.
📖 Inspiration
After heartfelt conversations with our grandparents and other elderly individuals, we learned that loneliness, lack of purpose, and cognitive decline are among the most challenging aspects of aging. These conversations inspired us to create a compassionate, user-friendly solution that:
- Helps track cognitive and emotional health
- Facilitates meaningful connections with loved ones and peers
- Provides an engaging, accessible experience for all users
✨ Features
🎮 Daily Brain & Mood Games
Interactive exercises inspired by clinical assessments like the Stroop Test and List Recall games to evaluate:
- Attention span
- Memory retention
- Reaction speed
- Cognitive flexibility
📊 Progress Tracking Dashboard
Intuitive visual summaries that display:
- Performance trends over time
- Cognitive improvement metrics
- Mood tracking insights
🤝 Connection Mode
A social circle feature enabling users to:
- Share game results with family and friends
- Send messages and stay connected
- Build a supportive community
🎲 Multiplayer Games with LLM Facilitation
- Play cooperatively or competitively with friends
- AI-powered game host provides conversational, friendly guidance
- Adaptive difficulty based on player performance
♿ Accessibility for the Visually Impaired
- Fish Audio API integration for speech-based interactions
- Audio feedback for all tasks and game results
- Full accessibility for users with limited vision
🛠️ Tech Stack
Frontend
- React Native (cross-platform mobile: iOS & Android)
Backend
- Node.js
- Express.js
- JWT authentication for secure sessions
Database
- MongoDB (scalable, secure user data storage)
AI & Audio
- JanitorAI API (conversational game facilitation)
- Fish Audio API (text-to-speech for accessibility)
Additional Tools
- Real-time communication for multiplayer features
- Adaptive LLM prompts for personalized difficulty
🚀 Getting Started
Prerequisites
- Node.js (v14 or higher)
- MongoDB
- npm or yarn
- React Native development environment
Installation
- Clone the repository
git clone https://github.com/yourusername/eldercare-app.git
cd eldercare-app
- Install backend dependencies
cd backend
npm install
- Install frontend dependencies
cd ../frontend
npm install
- Configure environment variables
Create a
.envfile in the backend directory:
MONGODB_URI=your_mongodb_connection_string
JWT_SECRET=your_jwt_secret
JANITOR_AI_API_KEY=your_janitorai_key
FISH_AUDIO_API_KEY=your_fish_audio_key
PORT=8000
- Start the backend server
cd backend
npm start
- Start the React Native app
cd frontend
npm start
# For iOS
npm run ios
# For Android
npm run android
📱 Usage
- Create an account or log in
- Complete daily brain games to track cognitive performance
- Check your dashboard for progress insights
- Connect with family through the social circle feature
- Play multiplayer games with friends using the LLM-facilitated game mode
🔧 Challenges We Overcame
Accessibility Design
Ensuring games were equally usable for both sighted and visually impaired users required extensive experimentation with audio feedback timing and clarity.
LLM Integration
Calibrating the language model to act as a friendly, helpful "game host" without overwhelming or confusing users was a significant UX challenge that required careful prompt engineering.
Data Visualization
Creating intuitive, non-overwhelming visual representations of cognitive trends for older users took multiple design iterations and user testing.
💡 What We Learned
- How technology can bridge generational gaps when designed with empathy and accessibility as core principles
- Best practices for integrating audio-based AI models for accessibility
- Techniques for real-time multiplayer state management
- The importance of designing for underserved user demographics
🙏 Acknowledgments
- Our grandparents and elderly community members who shared their experiences
- Fish Audio for accessibility API support
- JanitorAI for conversational AI capabilities
- The open-source community for invaluable tools and resources
Analysis
View
Metric
- 9
Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.
Technology
- JavaScriptIn code
- PythonIn code
- ReactIn code
- TypeScriptIn code
- MongoDBClaimed
- Node.jsClaimed
4 of 6 appear in the indexed code. 2 claimed on Devpost could not be matched to code, which may simply mean the tool leaves no trace in the repository.
AI coding agents
No AI coding agent signals were found in this repository.
Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.
Codebase size
Source size
158 KB
Source files
35
Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.
Repository
anika213/calhacks
54 files · 2.5 MB · @ 395dc73
Structure
Interface
24 files · 44%Screens, components and styles rendered to the user.
Application logic
8 files · 15%Domain rules, services and shared utilities.
Supporting
Layers are inferred from where files sit in the tree, not from reading the code. A project that names its directories unconventionally will read oddly here — open the file browser to check anything the diagram implies.
Languages
- TypeScript82%
- JavaScript14%
- Markdown4%
- Python0%
Share of indexed source by file size. Binary and vendored files are excluded.
Dependencies
frontend/package.json
npm · 34- @expo/vector-icons
- @react-native-async-storage/async-storage
- @react-native-picker/picker
- @react-navigation/bottom-tabs
- @react-navigation/elements
- @react-navigation/native
- expo
- expo-blur
- expo-constants
- expo-font
- expo-haptics
- expo-image
- expo-linear-gradient
- expo-linking
- expo-router
- expo-splash-screen
- expo-status-bar
- expo-symbols
- +16 more
Declared in the repository’s manifests at the indexed commit. A declared package is not proof it is used, and runtime dependencies are listed first.
This project’s features have not been analysed yet.
Export this project's context (description, README, evidence, key source files) to chat with an AI agent elsewhere.