1. Overview
2. System Architecture
3. Core Components
4. Technical Stack
5. Installation and Setup
6. Development Guidelines
7. API Documentation
8. Security and Compliance
9. Deployment
10. Contributing
11. License

iCare Central is a comprehensive system that combines AI-powered wheelchair navigation with health monitoring capabilities. The system uses eye tracking technology for wheelchair control and integrates various sensors for health monitoring, creating a unified platform for mobility assistance and health oversight.

• AI-powered eye tracking for wheelchair navigation
• Real-time obstacle detection
• Stability monitoring
• Emergency stop protocols
• Battery monitoring

• Integrated vital monitoring sensors
• Heart rate variability analysis using camera-based technology
• Real-time health alerts
• Activity monitoring
• Emergency response integration

The system follows a modular architecture with components for both wheelchair control and health monitoring:

icare-central/
├── care-app/           # Main control and monitoring interface
├── cam_hrv/           # Camera-based health monitoring
├── eye_tracking/      # AI eye tracking for navigation
├── icare-imu/         # IMU integration for stability
├── icare-mongo/       # Health and usage data management
├── icare-nav/         # Navigation and safety systems
└── icare-patient/     # Health management system

The main interface that provides:

• Wheelchair control dashboard
• Health data visualization
• System configuration
• Sensor integration
• Health monitoring interface

Health monitoring system that:

• Uses camera-based photoplethysmography (PPG)
• Processes video streams in real-time
• Calculates HRV metrics
• Provides continuous health monitoring
• Integrates with mobility controls

Navigation system that:

• Tracks eye movements using deep learning
• Translates gaze patterns into wheelchair commands
• Provides navigation control
• Includes safety features
• Adapts to user patterns

Movement monitoring system that:

• Tracks wheelchair movement and position
• Monitors stability and tilt
• Detects potential falls
• Provides movement analytics
• Alerts caregivers of issues

Data management system that:

• Stores health and mobility data
• Manages system configurations
• Handles data backup and recovery
• Provides secure data access
• Ensures data integrity

Mobility system that:

• Processes AI eye tracking commands
• Implements obstacle detection
• Manages movement patterns
• Integrates safety systems
• Provides navigation assistance

Health platform that:

• Manages user health profiles
• Tracks medical history
• Processes health monitoring data
• Manages emergency contacts
• Generates health reports

The caregiver interface provides tools for monitoring and assistance:

• Real-time wheelchair location and status
• Live vital signs monitoring
• Health trend analysis
• Emergency alerts
• Battery and system status
• Usage statistics

• Health profiles
• Medical history access
• Emergency contact information
• Care schedule management
• Activity logs

• Live health data feed
• Vital signs trends
• Movement patterns
• Fall detection
• Custom health alerts

• Direct patient messaging
• Emergency broadcast
• Care team coordination
• Family updates
• Emergency protocols

The patient interface combines mobility control with health monitoring:

• AI eye tracking calibration
• Movement sensitivity settings
• Emergency controls
• Location management
• Route planning

• Personal vital signs
• Activity tracking
• Progress reports
• Emergency contacts

• Obstacle warnings
• Fall prevention
• Battery monitoring
• Emergency assistance
• Location sharing

• Caregiver messaging
• Emergency alerts
• Family updates
• Care team contact
• Voice commands

• High contrast mode
• Voice navigation
• Customizable display
• Screen reader support
• Gesture controls

• Comprehensive monitoring
• Efficient care coordination
• Quick emergency response
• Data-driven decisions
• Enhanced patient safety

• Enhanced independence
• Intuitive wheelchair control
• Real-time health monitoring
• Improved safety
• Better communication

• React.js for the control interface
• Material-UI for component design
• Redux for state management
• WebSocket for real-time communication
• Chart.js for data visualization
• TensorFlow.js for AI processing

• Node.js for server-side operations
• Express.js for API endpoints
• MongoDB for data storage
• Python for AI/ML components
• WebSocket for real-time updates
• TensorFlow for eye tracking AI

• Docker for containerization
• AWS for cloud hosting
• CI/CD pipeline with GitHub Actions
• Monitoring with Prometheus and Grafana

• Node.js (v14 or higher)
• Python 3.8+
• MongoDB 4.4+
• Docker and Docker Compose
• Git

1. Clone the repository:

git clone https://github.com/yourusername/icare-central.git
cd icare-central

2. Install dependencies:

# Main application
cd care-app
npm install

# Python components
cd ../cam_hrv
pip install -r requirements.txt

3. Configure environment variables: Create a .env file in the root directory:

# Database Configuration
MONGODB_URI=mongodb://localhost:27017/icare
MONGODB_USER=your_username
MONGODB_PASSWORD=your_password

# Application Configuration
NODE_ENV=development
PORT=3000
API_KEY=your_api_key

# Security
JWT_SECRET=your_jwt_secret
ENCRYPTION_KEY=your_encryption_key

4. Start the development servers:

# Start MongoDB
docker-compose up -d mongodb

# Start the main application
cd care-app
npm run dev

# Start Python components
cd ../cam_hrv
python main.py

• Follow ESLint configuration for JavaScript/TypeScript
• Use Prettier for code formatting
• Follow PEP 8 for Python code
• Maintain consistent documentation

1. Create feature branches from development
2. Use conventional commits
3. Require code review before merging
4. Maintain clean commit history

• Unit tests for all components
• Integration tests for API endpoints
• End-to-end testing for critical paths
• Performance testing for real-time components

GET /api/patients
POST /api/patients
GET /api/patients/:id
PUT /api/patients/:id
DELETE /api/patients/:id

GET /api/monitoring/:patientId
POST /api/monitoring/data
GET /api/monitoring/alerts

GET /api/config
PUT /api/config
POST /api/config/backup

• patient:update - Real-time patient data updates
• alert:new - New alert notifications
• system:status - System status updates

• JWT-based authentication
• Role-based access control
• Data encryption at rest and in transit
• Regular security audits
• Input validation and sanitization
• Emergency override protocols
• Secure wheelchair control systems

• HIPAA compliance
• GDPR compliance
• Data retention policies
• Audit logging
• Regular compliance reviews
• Medical device regulations
• Accessibility standards

1. Build the application:

cd care-app
npm run build

2. Deploy using Docker:

docker-compose -f docker-compose.prod.yml up -d

• Application metrics
• System health checks
• Error tracking
• Performance monitoring
• Resource utilization

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

• Follow the coding standards
• Write comprehensive tests
• Update documentation
• Create detailed PR descriptions
• Address review comments

This project is licensed under the MIT License - see the LICENSE file for details.

For support, please contact:

• Technical Support: HD7946@wayne.edu
• Security Issues: Tlatelpa@wayne.edu
• Sales Inquiries: HO5863@wayne.edu
• General Inquiries: rkanna@wayne.edu

• Medical staff and healthcare professionals who provided input
• Open-source community for various tools and libraries
• Development team and contributors
• Healthcare institutions for testing and feedback
• Wheelchair users who provided valuable feedback
• AI/ML researchers and developers
• Accessibility experts and consultants