Real-Time Remote Patient Monitoring and Alarming System for Noncommunicable Lifestyle Diseases

Telemedicine and remote patient monitoring (RPM) systems have been gaining interest and received adaptation in healthcare sectors since the COVID-19 pandemic due to their efficiency and capability to deliver timely healthcare services while containing COVID-19 transmission. These systems were develo...

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Main Authors: Htet Yamin Ko Ko, Nitin Kumar Tripathi, Chitrini Mozumder, Sombat Muengtaweepongsa, Indrajit Pal
Format: Article
Language:English
Published: Hindawi Limited 2023-01-01
Series:International Journal of Telemedicine and Applications
Online Access:http://dx.doi.org/10.1155/2023/9965226
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author Htet Yamin Ko Ko
Nitin Kumar Tripathi
Chitrini Mozumder
Sombat Muengtaweepongsa
Indrajit Pal
author_facet Htet Yamin Ko Ko
Nitin Kumar Tripathi
Chitrini Mozumder
Sombat Muengtaweepongsa
Indrajit Pal
author_sort Htet Yamin Ko Ko
collection DOAJ
description Telemedicine and remote patient monitoring (RPM) systems have been gaining interest and received adaptation in healthcare sectors since the COVID-19 pandemic due to their efficiency and capability to deliver timely healthcare services while containing COVID-19 transmission. These systems were developed using the latest technology in wireless sensors, medical devices, cloud computing, mobile computing, telecommunications, and machine learning technologies. In this article, a real-time remote patient monitoring system is proposed with an accessible, compact, accurate, and low-cost design. The implemented system is designed to an end-to-end communication interface between medical practitioners and patients. The objective of this study is to provide remote healthcare services to patients who need ongoing care or those who have been discharged from the hospital without affecting their daily routines. The developed monitoring system was then evaluated on 1177 records from MIMIC-III clinical dataset (aged between 19 and 99 years). The performance analysis of the proposed system achieved 88.7% accuracy in generating alerts with logistic regression classification algorithm. This result reflects positively on the quality and robustness of the proposed study. Since the processing time of the proposed system is less than 2 minutes, it can be stated that the system has a high computational speed and is convenient to use in real-time monitoring. Furthermore, the proposed system will fulfil to cover the lower doctor-to-patient ratio by monitoring patients from remote locations and aged people who reside in their residences.
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spelling doaj.art-c84e6048bab44e84b14edc296bd1a6d02023-11-28T00:00:11ZengHindawi LimitedInternational Journal of Telemedicine and Applications1687-64232023-01-01202310.1155/2023/9965226Real-Time Remote Patient Monitoring and Alarming System for Noncommunicable Lifestyle DiseasesHtet Yamin Ko Ko0Nitin Kumar Tripathi1Chitrini Mozumder2Sombat Muengtaweepongsa3Indrajit Pal4Department of Information and Communication TechnologiesDepartment of Information and Communication TechnologiesDepartment of Information and Communication TechnologiesCenter of Excellence in StrokeSchool of EnvironmentTelemedicine and remote patient monitoring (RPM) systems have been gaining interest and received adaptation in healthcare sectors since the COVID-19 pandemic due to their efficiency and capability to deliver timely healthcare services while containing COVID-19 transmission. These systems were developed using the latest technology in wireless sensors, medical devices, cloud computing, mobile computing, telecommunications, and machine learning technologies. In this article, a real-time remote patient monitoring system is proposed with an accessible, compact, accurate, and low-cost design. The implemented system is designed to an end-to-end communication interface between medical practitioners and patients. The objective of this study is to provide remote healthcare services to patients who need ongoing care or those who have been discharged from the hospital without affecting their daily routines. The developed monitoring system was then evaluated on 1177 records from MIMIC-III clinical dataset (aged between 19 and 99 years). The performance analysis of the proposed system achieved 88.7% accuracy in generating alerts with logistic regression classification algorithm. This result reflects positively on the quality and robustness of the proposed study. Since the processing time of the proposed system is less than 2 minutes, it can be stated that the system has a high computational speed and is convenient to use in real-time monitoring. Furthermore, the proposed system will fulfil to cover the lower doctor-to-patient ratio by monitoring patients from remote locations and aged people who reside in their residences.http://dx.doi.org/10.1155/2023/9965226
spellingShingle Htet Yamin Ko Ko
Nitin Kumar Tripathi
Chitrini Mozumder
Sombat Muengtaweepongsa
Indrajit Pal
Real-Time Remote Patient Monitoring and Alarming System for Noncommunicable Lifestyle Diseases
International Journal of Telemedicine and Applications
title Real-Time Remote Patient Monitoring and Alarming System for Noncommunicable Lifestyle Diseases
title_full Real-Time Remote Patient Monitoring and Alarming System for Noncommunicable Lifestyle Diseases
title_fullStr Real-Time Remote Patient Monitoring and Alarming System for Noncommunicable Lifestyle Diseases
title_full_unstemmed Real-Time Remote Patient Monitoring and Alarming System for Noncommunicable Lifestyle Diseases
title_short Real-Time Remote Patient Monitoring and Alarming System for Noncommunicable Lifestyle Diseases
title_sort real time remote patient monitoring and alarming system for noncommunicable lifestyle diseases
url http://dx.doi.org/10.1155/2023/9965226
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