Towards symbolization using data-driven extraction of local trends for ICU monitoring.
We propose a methodology for the extraction of local trends from a stream of data. It has been designed to suit the needs of interpretation-oriented visualization and symbolization from ICU monitoring data. After giving implementation details for efficient computation of local trends, we propose the use of a characteristic analysis span for each variable. This characteristic span is obtained from a set of criteria that we compare and evaluate in regard of analysis of ICU monitoring data gathered within the Aiddaig project. The processing results in a rich visual representation and a framework for the local symbolization of the data stream based on its dynamics.
Calvelo
D
D
Laboratoire d'Automatique et Informatique Industrielle de Lille, Bâtiment P2 Cité Scientifique, Villeneuve d'Ascq, France. calvelo@lifl.fr
Chambrin
M C
MC
Pomorski
D
D
Ravaux
P
P
D001185:Artificial Intelligence; D006801:Humans; D007362:Intensive Care Units; D012815:Signal Processing, Computer-Assisted; D013561:Symbolism