From 88ac22c7f76f18ee31caaf30927754d24315e5e8 Mon Sep 17 00:00:00 2001 From: Francois Caud Date: Fri, 20 Dec 2024 14:43:58 +0100 Subject: [PATCH] DOC update README --- README.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 0a175c7..756ac69 100644 --- a/README.md +++ b/README.md @@ -1,14 +1,14 @@ -# Template Kit for RAMP challenge +# Non-invasive estimation of the MAP using PPG [![Build status](https://github.com/ramp-kits/template-kit/actions/workflows/test.yml/badge.svg)](https://github.com/ramp-kits/template-kit/actions/workflows/test.yml) ## Introduction -Describe the challenge, in particular: +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. -- Where the data comes from? -- What is the task this challenge aims to solve? -- Why does it matter? +Authors : Thomas Moreau (Inria), François Caud (DATAIA - Université Paris-Saclay), Jade Perdereau (APHP, Inria) ## Getting started