MindBloom

MindBloom is an interactive educational platform designed to help children with dyslexia through engaging games and screening tools. The application provides a comprehensive suite of games, progress tracking, and parental oversight to support early intervention and skill development.

Features

For Children

• Dyslexia Screening: Comprehensive assessment tools to identify potential dyslexia indicators
• Educational Games:
  • MemoryQuest: Memory enhancement exercises
  • MirrorMatch: Visual matching challenges
  • SoundSafari: Phonetic awareness activities
  • StoryWar: Narrative comprehension games
• Progress Tracking: Visual progress bars and skill charts
• Reward System: Achievement popups and motivation

For Parents

• Parent Dashboard: Monitor child's progress and performance
• Child Management: Add and manage multiple children
• Detailed Reports: Comprehensive progress reports and analytics
• Chatbot Support: AI-powered assistance for parents

Technical Features

• Real-time Gameplay: Interactive games with immediate feedback
• Cross-platform: Web-based application accessible on multiple devices
• Secure Authentication: Firebase-based user management
• Data Persistence: Supabase integration for data storage

Tech Stack

Frontend

• React 18 - Modern JavaScript library for building user interfaces
• Vite - Fast build tool and development server
• CSS3 - Styling with custom CSS and component-specific stylesheets
• Firebase - Authentication and real-time database

Backend

• Node.js - JavaScript runtime for server-side development
• Express.js - Web application framework
• Supabase - Open-source Firebase alternative for database and API

Machine Learning Services

• Python - Programming language for ML implementations
• Custom ML Models - Specialized algorithms for dyslexia assessment

Installation

Prerequisites

• Node.js (v16 or higher)
• Python (v3.8 or higher)
• npm or yarn package manager
• Git

Setup Instructions

1. Clone the repository

   git clone <repository-url>
   cd MindBloom

2. Frontend Setup

   cd frontend
   npm install

3. Server Setup

   cd ../server
   npm install

4. ML Services Setup

   cd ../ml_services
   pip install -r requirements.txt

Usage

Development

1. Start the ML Services

   cd ml_services
   python main.py

2. Start the Backend Server

   cd server
   npm start

3. Start the Frontend

   cd frontend
   npm run dev

4. Access the Application

   • Open your browser and navigate to http://localhost:5173 (or the port shown in the terminal)

Production Build

1. Build the Frontend

   cd frontend
   npm run build

2. Start Production Server

   cd server
   npm start

Project Structure

MindBloom/
├── frontend/          # React application
│   ├── src/
│   │   ├── components/    # Reusable UI components
│   │   ├── pages/         # Application pages/screens
│   │   ├── context/       # React context providers
│   │   ├── firebase/      # Firebase configuration
│   │   ├── services/      # API services and utilities
│   │   └── styles/        # CSS stylesheets
│   ├── public/            # Static assets
│   └── package.json
├── server/            # Node.js backend server
│   ├── server.js          # Main server file
│   ├── package.json       # Server dependencies
│   └── word_bank.json     # Word database
└── ml_services/       # Python ML services
    └── main.py            # ML processing scripts

API Documentation

The backend server provides RESTful APIs for:

• User authentication and management
• Game data and progress tracking
• Report generation
• ML service integration