Self-adaptative Early Warning Scoring System for Smart Hospital

Imen Ben Ida (1) , Moez Balti (1, 2) , Sondès Chaabane (3) , Abderrazak Jemai (1, 4)

1 SERCOM - Laboratoire Systèmes électroniques et réseaux de communications (Ecole polytechnique de Tunisie)
2 ISET'COM - Institute of Technology in Communications
3 LAMIH - Laboratoire d'Automatique, de Mécanique et d'Informatique industrielles et Humaines - UMR 8201
4 INSAT Carthage - Institut National des Sciences Appliquées et de Technologie - Carthage

With the advent of the Internet of Things (IoT), various interconnected objects can be used to improve the collection and the process of vital signs with partially or fully automatized methods in smart hospital environment. The vital signs data are used to evaluate patient health status using heuristic approaches, such as the early warning scoring (EWS) approach. Several applications have been proposed based on the early warning scores approach to improve the recognition of patients at risk of deterioration. However, there is a lack of efficient tools that enable a personalized monitoring depending on the patient situations. This paper explores the publish-subscribe pattern to provide a self-adaptative early warning score system in smart hospital context. We propose an adaptative configuration of the vital sings monitoring process depending on the patient health status variation and the medical staff decisions.

Mots clés: Computing for healthcare; Early warning scoring system; Internet of Things; Smart hospital

Domaines: Automatique / Robotique

Imen Ben Ida, Moez Balti, Sondès Chaabane, Abderrazak Jemai. Self-adaptative Early Warning Scoring System for Smart Hospital. 18th International Conference on Smart Homes and Health Telematics, ICOST 2020, Jun 2020, Hammamet, Tunisia. pp.16 - 27, ⟨10.1007/978-3-030-51517-1_2⟩. ⟨hal-03678338⟩