Non-invasive estimation of the MAP using PPG

Introduction

The continuous monitoring of blood pressure is a major challenge in the general anesthesia field. Indeed, the monitoring of blood pressure is essential to ensure that the patient is stable during the operation. However, the current methods to measure blood pressure are either non-invasive, but non-continuous, or invasive, which can lead to complications, and expensive, making them inadapted in many situations. A potential solution to this problem is to use non-invasive monitoring signals which are routinely collected, like the electrocardiogram (ECG) photoplethysmogram (PPG) signal, to estimate the mean arterial pressure (MAP) using AI. The PPG signal is a non-invasive signal that can be easily acquired using a pulse oximeter. The MAP is a measure of the average blood pressure in an individual's arteries during one cardiac cycle. The goal of this challenge is to estimate the MAP from the non-invasive signals.

Authors : Thomas Moreau (Inria), François Caud (DATAIA - Université Paris-Saclay), Jade Perdereau (APHP, Inria)

Getting started

Install

To run a submission and the notebook you will need the dependencies listed in requirements.txt. You can install the dependencies with the following command-line:

pip install -U -r requirements.txt

If you are using conda, we provide an environment.yml file for similar usage.

Challenge description

Get started on this RAMP with the dedicated notebook.

Test a submission

The submissions need to be located in the submissions folder. For instance for my_submission, it should be located in submissions/my_submission.

To run a specific submission, you can use the ramp-test command line:

ramp-test --submission my_submission

You can get more information regarding this command line:

ramp-test --help

To go further

You can find more information regarding ramp-workflow in the dedicated documentation