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Real-time tracking and detection of patient conditions in the intelligent m-Health monitoring system

In order to help patients monitor their personal health in real time, this paper proposes an intelligent mobile health monitoring system and establishes a corresponding health network to track and process patients' physical activity and other health-related factors in real time. Performance was...

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Autores principales: Li, Xiaoyan, You, Kangwon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9589418/
https://www.ncbi.nlm.nih.gov/pubmed/36299750
http://dx.doi.org/10.3389/fpubh.2022.922718
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author Li, Xiaoyan
You, Kangwon
author_facet Li, Xiaoyan
You, Kangwon
author_sort Li, Xiaoyan
collection PubMed
description In order to help patients monitor their personal health in real time, this paper proposes an intelligent mobile health monitoring system and establishes a corresponding health network to track and process patients' physical activity and other health-related factors in real time. Performance was analyzed. The experimental results show that after comparing the accuracy, delay time, error range, efficiency, and energy utilization of Im-HMS and existing UCD systems, it is found that the accuracy of Im-HMS is mostly between 98 and 100%, while the accuracy of UCD is mostly between 98 and 100%. Most of the systems are between 91 and 97%; in terms of delay comparison, the delay of the Im-HMS system is between 18 and 39 ms, which is far lower than the lowest value of the UCD system of 84 ms, and the Im-HMS is significantly better than the existing UCD system; the error range of Im-HMS is mainly between 0.2 and 1.4, while the error range of UCD system is mainly between −2 and 14; and in terms of efficiency and energy utilization, Im-HMS values are higher than those of UCD system. In general, the Im-HMS system proposed in this study is more accurate than UCD system and has lower delay, smaller error, and higher efficiency, and energy utilization is more efficient than UCD system, which is of great significance for mobile health monitoring in practical applications.
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spelling pubmed-95894182022-10-25 Real-time tracking and detection of patient conditions in the intelligent m-Health monitoring system Li, Xiaoyan You, Kangwon Front Public Health Public Health In order to help patients monitor their personal health in real time, this paper proposes an intelligent mobile health monitoring system and establishes a corresponding health network to track and process patients' physical activity and other health-related factors in real time. Performance was analyzed. The experimental results show that after comparing the accuracy, delay time, error range, efficiency, and energy utilization of Im-HMS and existing UCD systems, it is found that the accuracy of Im-HMS is mostly between 98 and 100%, while the accuracy of UCD is mostly between 98 and 100%. Most of the systems are between 91 and 97%; in terms of delay comparison, the delay of the Im-HMS system is between 18 and 39 ms, which is far lower than the lowest value of the UCD system of 84 ms, and the Im-HMS is significantly better than the existing UCD system; the error range of Im-HMS is mainly between 0.2 and 1.4, while the error range of UCD system is mainly between −2 and 14; and in terms of efficiency and energy utilization, Im-HMS values are higher than those of UCD system. In general, the Im-HMS system proposed in this study is more accurate than UCD system and has lower delay, smaller error, and higher efficiency, and energy utilization is more efficient than UCD system, which is of great significance for mobile health monitoring in practical applications. Frontiers Media S.A. 2022-10-10 /pmc/articles/PMC9589418/ /pubmed/36299750 http://dx.doi.org/10.3389/fpubh.2022.922718 Text en Copyright © 2022 Li and You. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Public Health
Li, Xiaoyan
You, Kangwon
Real-time tracking and detection of patient conditions in the intelligent m-Health monitoring system
title Real-time tracking and detection of patient conditions in the intelligent m-Health monitoring system
title_full Real-time tracking and detection of patient conditions in the intelligent m-Health monitoring system
title_fullStr Real-time tracking and detection of patient conditions in the intelligent m-Health monitoring system
title_full_unstemmed Real-time tracking and detection of patient conditions in the intelligent m-Health monitoring system
title_short Real-time tracking and detection of patient conditions in the intelligent m-Health monitoring system
title_sort real-time tracking and detection of patient conditions in the intelligent m-health monitoring system
topic Public Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9589418/
https://www.ncbi.nlm.nih.gov/pubmed/36299750
http://dx.doi.org/10.3389/fpubh.2022.922718
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