Self-adaptative Early Warning Scoring System for Smart Hospital

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.

[1]  Roger A. Light Mosquitto: server and client implementation of the MQTT protocol , 2017, J. Open Source Softw..

[2]  Meikang Qiu,et al.  Health-CPS: Healthcare Cyber-Physical System Assisted by Cloud and Big Data , 2017, IEEE Systems Journal.

[3]  Seth Kenlon,et al.  Getting Started with the Raspberry Pi , 2018, Developing Games on the Raspberry Pi.

[4]  Mingzhe Jiang,et al.  Exploiting smart e-Health gateways at the edge of healthcare Internet-of-Things: A fog computing approach , 2018, Future Gener. Comput. Syst..

[5]  Siobhán Clarke,et al.  Middleware for Internet of Things: A Survey , 2016, IEEE Internet of Things Journal.

[6]  Victor I. Chang,et al.  Towards fog-driven IoT eHealth: Promises and challenges of IoT in medicine and healthcare , 2018, Future Gener. Comput. Syst..

[7]  S. Salanterä,et al.  The Internet of Things for basic nursing care-A scoping review. , 2017, International journal of nursing studies.

[8]  Cristiano André da Costa,et al.  Internet of Health Things: Toward intelligent vital signs monitoring in hospital wards , 2018, Artif. Intell. Medicine.

[9]  R. Randell,et al.  Strengths and limitations of early warning scores: A systematic review and narrative synthesis. , 2017, International journal of nursing studies.

[10]  Hannu Tenhunen,et al.  Context-Aware Early Warning System for In-Home Healthcare Using Internet-of-Things , 2015, IoT 360.

[11]  Jianhua Ma,et al.  KID Model-Driven Things-Edge-Cloud Computing Paradigm for Traffic Data as a Service , 2018, IEEE Network.

[12]  Mingzhe Jiang,et al.  Low-cost fog-assisted health-care IoT system with energy-efficient sensor nodes , 2017, 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC).