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Remote diagnostic and detection of coronavirus disease (COVID-19) system based on intelligent healthcare and internet of things
In this paper, we will propose a novel system for remote detecting COVID-19 patients based on artificial intelligence technology and internet of things (IoT) in order to stop the virus spreading at an early stage. In this work, we will focus on connecting several sensors to work together as a system...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author(s). Published by Elsevier B.V.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7879050/ https://www.ncbi.nlm.nih.gov/pubmed/33614401 http://dx.doi.org/10.1016/j.rinp.2021.103910 |
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author | Elagan, S.K. Abdelwahab, Sayed F. Zanaty, E.A. Alkinani, Monagi H. Alotaibi, Hammad Zanaty, Mohammed E.A. |
author_facet | Elagan, S.K. Abdelwahab, Sayed F. Zanaty, E.A. Alkinani, Monagi H. Alotaibi, Hammad Zanaty, Mohammed E.A. |
author_sort | Elagan, S.K. |
collection | PubMed |
description | In this paper, we will propose a novel system for remote detecting COVID-19 patients based on artificial intelligence technology and internet of things (IoT) in order to stop the virus spreading at an early stage. In this work, we will focus on connecting several sensors to work together as a system that can discover people infected with the Coronavirus remotely, this will reduce the spread of the disease. The proposed system consists of several devices called smart medical sensors such as: pulse, thermal monitoring, and blood sensors. The system is working sequentially starting by pulse sensor and end by blood sensor including an algorithm to manage the data given from sensors. The pulse sensor is devoted to acquire a high quality data using a smartphone equipped by a mobile dermatoscope with 20× magnification. The processing is used RGB color system to perform moving window to segment regions of interest (ROIs) as inputs of the heart rate estimation algorithm. The heart rate (HR) estimation is then given by computing the dominant frequency by identifying the most prominent peak of the discrete Fourier transform (DFT) technique. The thermal monitoring is used for fever detection using a smart camera that can provide an optimum solution for fever detection. The infrared sensor can quickly measure surface temperature without making any contact with a person’s skin. A blood sensor is used to measure percentages of white, red blood (WBCs, RBCs) volume and platelets non-invasively using the bioimpedance analysis and independent component analysis (ICA). The proposed sensor consists of two electrodes which can be used to send the current to the earlobe and measure the produced voltage. A mathematical model was modified to describe the impedance of earlobe in different frequencies (i.e., low, medium, and high). The COMSOL model is used to simulate blood electrical properties and frequencies to measure WBCs, RBCs and Platelets volume. These devices are collected to work automatically without user interaction for remote checking the coronavirus patients. The proposed system is experimented by six examples to prove its applicability and efficiency. |
format | Online Article Text |
id | pubmed-7879050 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Author(s). Published by Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-78790502021-02-16 Remote diagnostic and detection of coronavirus disease (COVID-19) system based on intelligent healthcare and internet of things Elagan, S.K. Abdelwahab, Sayed F. Zanaty, E.A. Alkinani, Monagi H. Alotaibi, Hammad Zanaty, Mohammed E.A. Results Phys Article In this paper, we will propose a novel system for remote detecting COVID-19 patients based on artificial intelligence technology and internet of things (IoT) in order to stop the virus spreading at an early stage. In this work, we will focus on connecting several sensors to work together as a system that can discover people infected with the Coronavirus remotely, this will reduce the spread of the disease. The proposed system consists of several devices called smart medical sensors such as: pulse, thermal monitoring, and blood sensors. The system is working sequentially starting by pulse sensor and end by blood sensor including an algorithm to manage the data given from sensors. The pulse sensor is devoted to acquire a high quality data using a smartphone equipped by a mobile dermatoscope with 20× magnification. The processing is used RGB color system to perform moving window to segment regions of interest (ROIs) as inputs of the heart rate estimation algorithm. The heart rate (HR) estimation is then given by computing the dominant frequency by identifying the most prominent peak of the discrete Fourier transform (DFT) technique. The thermal monitoring is used for fever detection using a smart camera that can provide an optimum solution for fever detection. The infrared sensor can quickly measure surface temperature without making any contact with a person’s skin. A blood sensor is used to measure percentages of white, red blood (WBCs, RBCs) volume and platelets non-invasively using the bioimpedance analysis and independent component analysis (ICA). The proposed sensor consists of two electrodes which can be used to send the current to the earlobe and measure the produced voltage. A mathematical model was modified to describe the impedance of earlobe in different frequencies (i.e., low, medium, and high). The COMSOL model is used to simulate blood electrical properties and frequencies to measure WBCs, RBCs and Platelets volume. These devices are collected to work automatically without user interaction for remote checking the coronavirus patients. The proposed system is experimented by six examples to prove its applicability and efficiency. The Author(s). Published by Elsevier B.V. 2021-03 2021-02-12 /pmc/articles/PMC7879050/ /pubmed/33614401 http://dx.doi.org/10.1016/j.rinp.2021.103910 Text en © 2021 The Author(s) Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Elagan, S.K. Abdelwahab, Sayed F. Zanaty, E.A. Alkinani, Monagi H. Alotaibi, Hammad Zanaty, Mohammed E.A. Remote diagnostic and detection of coronavirus disease (COVID-19) system based on intelligent healthcare and internet of things |
title | Remote diagnostic and detection of coronavirus disease (COVID-19) system based on intelligent healthcare and internet of things |
title_full | Remote diagnostic and detection of coronavirus disease (COVID-19) system based on intelligent healthcare and internet of things |
title_fullStr | Remote diagnostic and detection of coronavirus disease (COVID-19) system based on intelligent healthcare and internet of things |
title_full_unstemmed | Remote diagnostic and detection of coronavirus disease (COVID-19) system based on intelligent healthcare and internet of things |
title_short | Remote diagnostic and detection of coronavirus disease (COVID-19) system based on intelligent healthcare and internet of things |
title_sort | remote diagnostic and detection of coronavirus disease (covid-19) system based on intelligent healthcare and internet of things |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7879050/ https://www.ncbi.nlm.nih.gov/pubmed/33614401 http://dx.doi.org/10.1016/j.rinp.2021.103910 |
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