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)

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