Mobile Health in Remote Patient Monitoring for Chronic Diseases: Principles, Trends, and Challenges

Nora El-Rashidy; Shaker El-Sappagh; S. Islam; Hazem M. El-Bakry; Samir Abdelrazek

doi:10.3390/diagnostics11040607

journal article Open Access Mar 29, 2021

Mobile Health in Remote Patient Monitoring for Chronic Diseases: Principles, Trends, and Challenges

Nora El-Rashidy

Shaker El-Sappagh

S. Islam

Hazem M. El-Bakry Samir Abdelrazek

Diagnostics Vol. 11 No. 4 pp. 607 · MDPI AG

View at Publisher Save 10.3390/diagnostics11040607

Abstract

Chronic diseases are becoming more widespread. Treatment and monitoring of these diseases require going to hospitals frequently, which increases the burdens of hospitals and patients. Presently, advancements in wearable sensors and communication protocol contribute to enriching the healthcare system in a way that will reshape healthcare services shortly. Remote patient monitoring (RPM) is the foremost of these advancements. RPM systems are based on the collection of patient vital signs extracted using invasive and noninvasive techniques, then sending them in real-time to physicians. These data may help physicians in taking the right decision at the right time. The main objective of this paper is to outline research directions on remote patient monitoring, explain the role of AI in building RPM systems, make an overview of the state of the art of RPM, its advantages, its challenges, and its probable future directions. For studying the literature, five databases have been chosen (i.e., science direct, IEEE-Explore, Springer, PubMed, and science.gov). We followed the (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) PRISMA, which is a standard methodology for systematic reviews and meta-analyses. A total of 56 articles are reviewed based on the combination of a set of selected search terms including RPM, data mining, clinical decision support system, electronic health record, cloud computing, internet of things, and wireless body area network. The result of this study approved the effectiveness of RPM in improving healthcare delivery, increase diagnosis speed, and reduce costs. To this end, we also present the chronic disease monitoring system as a case study to provide enhanced solutions for RPMs.

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Details

Published: Mar 29, 2021
Vol/Issue: 11(4)
Pages: 607
License: View

Authors

N

Nora El-Rashidy

Machine Learning and Information Retrieval Department, Faculty of Artificial Intelligence, Kafrelsheiksh University, Kafrelsheiksh 13518, Egypt

S

Shaker El-Sappagh

Centro Singular de Investigación en Tecnoloxías Intelixentes (CiTIUS), Universidade de Santiago de Compostela, 15782 Santiago de Compostela, Spain; Information Systems Department, Faculty of Computers and Artificial Intelligence, Benha University, Banha 13518, Egypt

S

S. Islam

Department of Computer Science and Engineering, Sejong University, Seoul 05006, Korea

H

Hazem M. El-Bakry

Information Systems Department, Faculty of Computers and Information, Mansoura University, Mansoura 13518, Egypt

S

Samir Abdelrazek

Information Systems Department, Faculty of Computers and Information, Mansoura University, Mansoura 13518, Egypt

Cite This Article

Nora El-Rashidy, Shaker El-Sappagh, S. Islam, et al. (2021). Mobile Health in Remote Patient Monitoring for Chronic Diseases: Principles, Trends, and Challenges. Diagnostics, 11(4), 607. https://doi.org/10.3390/diagnostics11040607

Mobile Health in Remote Patient Monitoring for Chronic Diseases: Principles, Trends, and Challenges

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