diff --git a/map_estimation_starting_kit.ipynb b/map_estimation_starting_kit.ipynb index d8da195..66d15b7 100644 --- a/map_estimation_starting_kit.ipynb +++ b/map_estimation_starting_kit.ipynb @@ -11,7 +11,7 @@ "\n", "# Non-invasive estimation of the MAP using PPG\n", "\n", - " Thomas Moreau (Inria) " + " Thomas Moreau (Inria), François Caud (DATAIA - Université Paris-Saclay) " ] }, { @@ -20,7 +20,7 @@ "source": [ "\n", "
\n", - "\"Monitor\n", + "\"Monitor\n", "
\n", "\n", "\n", @@ -30,14 +30,14 @@ "\n", "\n", "
\n", - "\"Cuff\n", + "\"Cuff\n", "
\n", "\n", "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.\n", "\n", "
\n", - "\"ECG\n", - "\"PPG\n", + "\"ECG\n", + "\"PPG\n", "
\n", "\n", "The goal of this challenge is to estimate the MAP from the non-invasive signals. The dataset consists of window of 10 seconds of PPG and ECG signals, with the related patient information (age, gender, weight, height, etc.) and the MAP measured with an invasive method.\n",