SonoSight - Glaucoma Detection App

An innovative Flutter application that uses ultrasound technology to measure intraocular pressure (IOP) for early glaucoma detection.

Overview

SonoSight addresses the critical problem of glaucoma detection through affordable, non-invasive IOP measurement using ultrasonic technology. The app connects to ESP8266-based hardware that measures IOP using acoustic radiation force (ARF).

Key Features

🎯 Main Features

• Real-time Dashboard: Live IOP readings from ESP8266 device with 3D interactive eye visualization
• Risk Analysis: AI-powered glaucoma risk assessment using camera input and multiple parameters
• Reading History: Complete history of IOP measurements with detailed analytics
• Settings: Device configuration and data management
• About: Information about SonoSight technology

📱 Pages

1. Dashboard Page

   • Current IOP display with status indicator
   • Interactive 3D eye model (rotatable and scalable)
   • Real-time sensor readings (ARF, Deformation, Resistance)
   • Device connection status
   • Start/Pause scan controls

2. Risk Analysis Page

   • Camera integration for eye image capture
   • AI model-based risk calculation
   • Circular gauge showing glaucoma risk score
   • Risk parameters visualization
   • Risk factors (Age, Family History, Diabetes, Blood Pressure)
   • Personalized recommendations

3. History Page

   • Chronological list of all readings
   • Detailed view for each reading
   • Status indicators
   • Export functionality

4. Settings Page

   • Bluetooth device configuration
   • Reading interval settings
   • Dark mode toggle
   • Data management
   • Version information

5. About Page

   • Technology overview
   • Problem statement
   • Solution details
   • Key advantages
   • Contact information

Technology Stack

• Framework: Flutter (Dart)
• State Management: Provider
• 3D Visualization: Custom Paint with vector_math
• Camera: camera package
• Charts: charts_flutter
• Networking: HTTP, Dio, flutter_bluetooth_serial
• Storage: SharedPreferences, SQLite
• UI: Material Design 3 with custom theming

Getting Started

Prerequisites

• Flutter SDK (3.0.0 or higher)
• Dart SDK
• Android Studio / VS Code with Flutter extensions
• Physical device or emulator

Installation

1. Clone the repository:

git clone <repository-url>
cd sonosight

2. Install dependencies:

flutter pub get

3. Run the app:

flutter run

Configuration

The app simulates ESP8266 connections by default. To connect to actual hardware:

1. Implement Bluetooth pairing in ESPProvider
2. Configure device UUID in settings
3. Update data parsing logic for your specific hardware protocol

Project Structure

lib/
├── main.dart                    # App entry point
├── screens/                     # Page screens
│   ├── home_screen.dart        # Main screen with bottom nav
│   ├── dashboard_page.dart     # Dashboard with 3D eye
│   ├── risk_calculation_page.dart  # Risk analysis page
│   ├── history_page.dart       # Reading history
│   ├── settings_page.dart      # Settings
│   └── about_page.dart         # About page
├── widgets/                     # Reusable widgets
│   ├── eye_visualization.dart  # 3D reconstruction widget
│   ├── risk_gauge.dart prediction gauge
│   ├── metric_card.dart        # Metric display card
│   └── connection_status.dart  # Connection indicator
├── providers/                   # State management
│   ├── esp_provider.dart       # ESP8266 communication
│   ├── camera_provider.dart    # Camera functionality
│   └── risk_provider.dart      # Risk calculation
└── theme/                       # UI theme
    └── app_theme.dart          # Theme configuration

Features Explained

1. 3D Eye Visualization

The interactive eye model:

• Draggable rotation
• Pinch-to-zoom scaling
• Wireframe/solid view toggle
• Real-time updates based on sensor data

2. AI Risk Assessment

Risk calculation considers:

• IOP Level (40% weight)
• Age (20% weight)
• Blood Pressure (15% weight)
• Family History (15% weight)
• Diabetes (10% weight)

3. ESP8266 Communication

Simulates real-time data stream:

• ARF (Acoustic Radiation Force) measurements
• Deformation calculations
• Resistance computation
• IOP derivation

UI/UX Highlights

• Modern Design: Clean, professional interface
• Color-coded Status: Visual indicators for IOP levels
• Interactive Elements: Gesture-based controls
• Dark Mode Support: System-based theming
• Responsive Layout: Adapts to different screen sizes
• Smooth Animations: Fluid transitions and effects

IOP Status Levels

• Low (< 12 mmHg): Blue indicator
• Normal (12-21 mmHg): Green indicator
• Elevated (21-30 mmHg): Orange indicator
• High (> 30 mmHg): Red indicator - Consult doctor

Future Enhancements

• Integration with actual ESP8266 hardware
• Cloud sync for reading history
• Multi-language support
• Enhanced AI model integration
• Patient profile management
• Telemedicine integration
• Export reports (PDF)
• Offline mode

License

All rights reserved - SonoSight Team

Contact

For questions or support, please reach out to the SonoSight team.

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Note: This is a demonstration app. Actual ESP8266 integration requires hardware implementation and proper calibration.