A4 Refereed article in a conference publication
Enhancing the Early Warning Score System Using Data Confidence
Authors: Maximilian Götzinger, Nima Taherinejad, Amir M. Rahmani, Pasi Liljeberg, Axel Jantsch, Hannu Tenhunen
Editors: Paolo Perego, Giuseppe Andreoni, Giovanna Rizzo
Conference name: International Conference on Wireless Mobile Communication and Healthcare
Publication year: 2017
Book title : Wireless Mobile Communication and Healthcare: 6th International Conference, MobiHealth 2016, Milan, Italy, November 14-16, 2016, Proceedings
Series title: Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
Volume: 192
First page : 91
Last page: 99
ISBN: 978-3-319-58876-6
eISBN: 978-3-319-58877-3
DOI: https://doi.org/10.1007/978-3-319-58877-3_12
Web address : https://link.springer.com/chapter/10.1007/978-3-319-58877-3_12
Early Warning Score (EWS) systems are utilized in hospitals by health-care professionals to interpret vital signals of patients. These scores are used to measure and predict amelioration or deterioration of patients’ health status to intervene in an appropriate manner when needed. Based on an earlier work presenting an automated Internet-of-Things based EWS system, we propose an architecture to analyze and enhance data reliability and consistency. In particular, we present a hierarchical agent-based data confidence evaluation system to detect erroneous or irrelevant vital signal measurements. In our extensive experiments, we demonstrate how our system offers a more robust EWS monitoring system.
