Neonatal Sleep Monitoring using Optical Flow (RAFT)

Introduction

This project aims to develop a system for monitoring sleep in neonates using optical flow techniques, particularly the RAFT (Optical Flow with Occlusions) algorithm. Neonatal sleep monitoring is crucial for assessing the health and well-being of infants in neonatal intensive care units (NICUs) and can provide valuable insights into their development and potential issues.

Features

• Non-invasive monitoring of neonatal sleep patterns
• High temporal resolution for detailed analysis of movement patterns and sleep stages
• Accuracy in motion estimation, even in challenging scenarios such as occlusions
• Real-time monitoring capabilities
• Objective assessment of sleep stages through quantified movement patterns
• Early identification of conditions like sleep apnea through abnormal sleep patterns
• Support for longitudinal studies by enabling continuous and automated monitoring over extended periods

Requirements

• Python 3.x
• OpenCV
• NumPy
• RAFT (Optical Flow with Occlusions) library
• Webcam or camera for capturing neonatal sleep footage

Installation

1. Clone the repository:

2. Install dependencies:

3. Download and install the RAFT library from here.

Usage

1. Connect a webcam or camera to your system.

2. Run the main script

3. Follow the on-screen instructions to start the neonatal sleep monitoring process.

Contributing

Contributions are welcome! If you would like to contribute to this project, please fork the repository and submit a pull request with your changes.

Acknowledgments

• This project was inspired by the need for non-invasive methods of monitoring neonatal sleep.
• Special thanks to the creators and contributors of the RAFT algorithm for providing a robust optical flow solution.