Correlation analysis of vital signs to monitor disease risks in ubiquitous healthcare system

Murtaza, H., Iqbal, M. A., Abbasi, Q. H. , Hussain, S. , Xing, H. and Imran, M. A. (2020) Correlation analysis of vital signs to monitor disease risks in ubiquitous healthcare system. EAI Endorsed Transactions on Industrial Networks and Intelligent Systems, 7(24), e1. (doi: 10.4108/eai.18-5-2020.165676)

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Abstract

Healthcare systems for chronic diseases demand continuous monitoring of physiological parameters or vital signs of the patients’ body. Through these vital signs’ information, healthcare experts attempt to diagnose the behavior of a disease. Identifying the relationship between these vital signs is still a big question for the research community. We have proposed a sophisticated way to identify the affiliations between vital signs of three specific diseases i.e., Sepsis, Sleep Apnea, and Intradialytic Hypotension (IDH) through Pearson statistical correlation analysis. Vital signs data of about 32 patients were taken for analysis. Experimental results show significant affiliations of vital signs of Sepsis and IDH with average correlation coefficient of 0.9 and 0.58, respectively. The stability of the mentioned correlation is about 75% and 90%, respectively.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Imran, Professor Muhammad and Hussain, Dr Sajjad and Abbasi, Professor Qammer
Authors: Murtaza, H., Iqbal, M. A., Abbasi, Q. H., Hussain, S., Xing, H., and Imran, M. A.
College/School:College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering
College of Science and Engineering > School of Engineering > Systems Power and Energy
Journal Name:EAI Endorsed Transactions on Industrial Networks and Intelligent Systems
Publisher:European Alliance for Innovation
ISSN:2410-0218
ISSN (Online):2410-0218
Published Online:27 July 2020
Copyright Holders:Copyright © 2020 Hassan Murtaza et al.
First Published:First published in EAI Endorsed Transactions on Industrial Networks and Intelligent Systems 7(24): e1
Publisher Policy:Reproduced under a Creative Commons license

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