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ICU Multi-Vital Signal Monitor

Introduction

Welcome to the ICU Multi-Vital Signal Monitor project! This innovative desktop application re-imagines how healthcare professionals monitor vital signals in intensive care units (ICUs). Leveraging the power of Python and Qt, this innovative tool provides a dynamic platform for visualizing and analyzing critical medical signals like ECG, EMG, EEG, and more.

With features like synchronized dual graphs, real-time cinematic playback, and customizable signal parameters, the ICU Signal Sentinel equips clinicians with enhanced insights, enabling them to make informed decisions and deliver timely interventions for improved patient outcomes. Whether it's tracking normal and abnormal signal patterns or generating detailed reports, the ICU Signal Sentinel is set to become an invaluable asset in modern healthcare settings.

Preview

Animation Gif

Features

Signal Selection

  • Browse your PC for signal files.
  • Explore three distinct medical signals, each with normal and abnormal examples.

Twin Graphs

  • Dual identical graphs with independent controls.
  • Synchronize both graphs with a single click.

Cinematic Experience

  • Signals play in real-time, just like ICU monitors.
  • Use rewind option to replay signals.

Signal Customization

  • Color Magic: Personalize signal colors.
  • Name That Signal: Add labels for clarity.
  • Hide & Seek: Show/hide signals on the fly.
  • Speed Dial: Control cine speed.
  • Zoom Wizard: Zoom in/out for precision.

Navigation Nirvana

  • Control the Narrative: Pause, play, or rewind signals.
  • Scroll & Pan Master: Scroll via sliders, pan with mouse movements.

Signal Management

  • Seamlessly move signals between graphs for comparison.

Exporting & Reporting

  • Construct professional PDF reports with snapshots and data statistics.

Contributors

Gratitude goes out to all team members for their valuable contributions to this project.

Acknowledgments

This project was supervised by Dr. Tamer Basha, who provided invaluable guidance and expertise throughout its development as a part of the Digital Signal Processing course at Cairo University Faculty of Engineering.

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  • Python 100.0%