Pose-estimation-for-Ergonomics

🧍 AI-Powered Posture Detector - Real-Time Ergonomics Tracker Detect poor posture in real-time using computer vision and help improve your desk ergonomics!

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🧍 AI-Powered Posture Detector

A real-time pose estimation tool that detects poor posture using computer vision to help improve ergonomics at your desk.

🎯 Overview

This project uses MediaPipe pose estimation to analyze your posture in real-time, providing instant feedback on whether you're maintaining good posture or slouching. Perfect for remote workers, students, or anyone who spends long hours at a desk.

Screenshot 2025-08-12 at 8 11 31 PM

Screenshot 2025-08-12 at 8 10 17 PM

✨ Features

  • Real-time Pose Detection: Uses MediaPipe to detect 33 body landmarks
  • Posture Analysis: Calculates neck and shoulder angles to determine posture quality
  • Visual Feedback: Color-coded feedback (Green = Good, Red = Slouching)
  • Live Statistics: Track your posture duration and percentages
  • Two Interfaces:
    • Command-line interface (main.py)
    • Web dashboard (streamlit_app.py)
  • Posture Lines: Visual overlay showing neck and spine alignment
  • Session Tracking: Monitor your posture habits over time

🛠️ Tech Stack

Component Technology
Pose Estimation MediaPipe
Computer Vision OpenCV
Web Interface Streamlit
Data Visualization Plotly
Language Python 3.8+

📦 Installation

  1. Clone the repository

    git clone [<repository-url>](https://github.com/ghaly-jd/Pose-estimation-for-Ergonomics)
cd Pose-estimation-for-Ergonomics

  2. Install dependencies

    pip install -r requirements.txt

  3. Verify installation

    python -c "import cv2, mediapipe, streamlit; print('✅ All dependencies installed!')"

🚀 Usage

Option 1: Command Line Interface

Run the basic posture detector:

python main.py

Controls:

  • Press q to quit
  • Sit at your desk facing the camera
  • Watch for color-coded feedback

Option 2: Streamlit Dashboard

Run the enhanced web interface:

streamlit run streamlit_app.py

Features:

  • Start/Stop detection with buttons
  • Real-time statistics and charts
  • Posture duration tracking
  • Interactive visualizations

📊 How It Works

Posture Classification Logic

Good Posture Criteria:

  • Neck angle < 45° (head not tilted too far forward)
  • Shoulder alignment < 15° (shoulders level)
  • Back relatively straight

Poor Posture Indicators:

  • Head tilting forward (neck angle > 45°)
  • Shoulders hunched or uneven
  • Spine not aligned

Key Measurements

  1. Neck Angle: Calculated from ear → shoulder → hip
  2. Shoulder Angle: Horizontal alignment of shoulders
  3. Posture Duration: Time spent in each posture state

🎥 Demo

To create a demo video:

  1. Record your session using screen recording software
  2. Show the interface with live posture detection
  3. Demonstrate posture changes (sit straight, then slouch)
  4. Highlight the feedback (color changes, angle measurements)

📈 Features Breakdown

✅ Completed

  • [x] Live webcam pose detection
  • [x] Calculate key angles (neck, shoulder)
  • [x] Classify posture (upright vs slouching)
  • [x] Display real-time feedback
  • [x] Visual posture lines overlay
  • [x] Session statistics tracking
  • [x] Dual interface options

🔄 Stretch Goals (Future)

  • [ ] Alert sounds after prolonged bad posture
  • [ ] CSV export of posture logs
  • [ ] Multiple camera support
  • [ ] Mobile app version
  • [ ] Machine learning model training

🎛️ Configuration

Adjustable Parameters

In main.py and streamlit_app.py, you can modify:

# Posture thresholds
self.NECK_ANGLE_THRESHOLD = 45  # degrees
self.SHOULDER_ANGLE_THRESHOLD = 15  # degrees

# Detection confidence
min_detection_confidence=0.5
min_tracking_confidence=0.5

Customization Tips

  • Lower thresholds = More sensitive detection
  • Higher thresholds = Less sensitive, fewer false positives
  • Adjust confidence = Balance between accuracy and performance

🐛 Troubleshooting

Common Issues

  1. Webcam not found

    # Check available cameras
python -c "import cv2; print([i for i in range(10) if cv2.VideoCapture(i).isOpened()])"

  2. Performance issues

    • Reduce frame resolution
    • Lower detection confidence
    • Close other applications

  3. Dependencies not found

    pip install --upgrade pip
pip install -r requirements.txt --force-reinstall

System Requirements

  • OS: Windows, macOS, or Linux
  • Python: 3.8 or higher
  • Camera: Built-in webcam or USB camera
  • RAM: 4GB+ recommended
  • GPU: Optional (CPU works fine)

📁 Project Structure

Pose-estimation-for-Ergonomics/
├── main.py              # Command-line posture detector
├── streamlit_app.py     # Web dashboard interface
├── requirements.txt     # Python dependencies
├── README.md           # This file
└── .gitignore          # Git ignore file

🤝 Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Add tests if applicable
  5. Submit a pull request

📄 License

This project is open source and available under the MIT License.

🙏 Acknowledgments

  • MediaPipe for pose estimation capabilities
  • OpenCV for computer vision tools
  • Streamlit for the web interface framework

📞 Support

If you encounter any issues or have questions:

  1. Check the troubleshooting section above
  2. Search existing issues
  3. Create a new issue with details about your problem

Happy Posture Monitoring! 🧍‍♂️✨

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