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Secure Health Monitoring Communication Systems Based on IoT and Cloud Computing for Medical Emergency Applications

Smart health surveillance technology has attracted wide attention between patients and professionals or specialists to provide early detection of critical abnormal situations without the need to be in direct contact with the patient. This paper presents a secure smart monitoring portable multivital...

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Autores principales: Siam, Ali I., Almaiah, Mohammed Amin, Al-Zahrani, Ali, Elazm, Atef Abou, El Banby, Ghada M., El-Shafai, Walid, El-Samie, Fathi E. Abd, El-Bahnasawy, Nirmeen A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8687823/
https://www.ncbi.nlm.nih.gov/pubmed/34938329
http://dx.doi.org/10.1155/2021/8016525
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author Siam, Ali I.
Almaiah, Mohammed Amin
Al-Zahrani, Ali
Elazm, Atef Abou
El Banby, Ghada M.
El-Shafai, Walid
El-Samie, Fathi E. Abd
El-Bahnasawy, Nirmeen A.
author_facet Siam, Ali I.
Almaiah, Mohammed Amin
Al-Zahrani, Ali
Elazm, Atef Abou
El Banby, Ghada M.
El-Shafai, Walid
El-Samie, Fathi E. Abd
El-Bahnasawy, Nirmeen A.
author_sort Siam, Ali I.
collection PubMed
description Smart health surveillance technology has attracted wide attention between patients and professionals or specialists to provide early detection of critical abnormal situations without the need to be in direct contact with the patient. This paper presents a secure smart monitoring portable multivital signal system based on Internet-of-Things (IoT) technology. The implemented system is designed to measure the key health parameters: heart rate (HR), blood oxygen saturation (SpO(2)), and body temperature, simultaneously. The captured physiological signals are processed and encrypted using the Advanced Encryption Standard (AES) algorithm before sending them to the cloud. An ESP8266 integrated unit is used for processing, encryption, and providing connectivity to the cloud over Wi-Fi. On the other side, trusted medical organization servers receive and decrypt the measurements and display the values on the monitoring dashboard for the authorized specialists. The proposed system measurements are compared with a number of commercial medical devices. Results demonstrate that the measurements of the proposed system are within the 95% confidence interval. Moreover, Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Mean Relative Error (MRE) for the proposed system are calculated as 1.44, 1.12, and 0.012, respectively, for HR, 1.13, 0.92, and 0.009, respectively, for SpO(2), and 0.13, 0.11, and 0.003, respectively, for body temperature. These results demonstrate the high accuracy and reliability of the proposed system.
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spelling pubmed-86878232021-12-21 Secure Health Monitoring Communication Systems Based on IoT and Cloud Computing for Medical Emergency Applications Siam, Ali I. Almaiah, Mohammed Amin Al-Zahrani, Ali Elazm, Atef Abou El Banby, Ghada M. El-Shafai, Walid El-Samie, Fathi E. Abd El-Bahnasawy, Nirmeen A. Comput Intell Neurosci Research Article Smart health surveillance technology has attracted wide attention between patients and professionals or specialists to provide early detection of critical abnormal situations without the need to be in direct contact with the patient. This paper presents a secure smart monitoring portable multivital signal system based on Internet-of-Things (IoT) technology. The implemented system is designed to measure the key health parameters: heart rate (HR), blood oxygen saturation (SpO(2)), and body temperature, simultaneously. The captured physiological signals are processed and encrypted using the Advanced Encryption Standard (AES) algorithm before sending them to the cloud. An ESP8266 integrated unit is used for processing, encryption, and providing connectivity to the cloud over Wi-Fi. On the other side, trusted medical organization servers receive and decrypt the measurements and display the values on the monitoring dashboard for the authorized specialists. The proposed system measurements are compared with a number of commercial medical devices. Results demonstrate that the measurements of the proposed system are within the 95% confidence interval. Moreover, Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Mean Relative Error (MRE) for the proposed system are calculated as 1.44, 1.12, and 0.012, respectively, for HR, 1.13, 0.92, and 0.009, respectively, for SpO(2), and 0.13, 0.11, and 0.003, respectively, for body temperature. These results demonstrate the high accuracy and reliability of the proposed system. Hindawi 2021-12-13 /pmc/articles/PMC8687823/ /pubmed/34938329 http://dx.doi.org/10.1155/2021/8016525 Text en Copyright © 2021 Ali I. Siam et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Siam, Ali I.
Almaiah, Mohammed Amin
Al-Zahrani, Ali
Elazm, Atef Abou
El Banby, Ghada M.
El-Shafai, Walid
El-Samie, Fathi E. Abd
El-Bahnasawy, Nirmeen A.
Secure Health Monitoring Communication Systems Based on IoT and Cloud Computing for Medical Emergency Applications
title Secure Health Monitoring Communication Systems Based on IoT and Cloud Computing for Medical Emergency Applications
title_full Secure Health Monitoring Communication Systems Based on IoT and Cloud Computing for Medical Emergency Applications
title_fullStr Secure Health Monitoring Communication Systems Based on IoT and Cloud Computing for Medical Emergency Applications
title_full_unstemmed Secure Health Monitoring Communication Systems Based on IoT and Cloud Computing for Medical Emergency Applications
title_short Secure Health Monitoring Communication Systems Based on IoT and Cloud Computing for Medical Emergency Applications
title_sort secure health monitoring communication systems based on iot and cloud computing for medical emergency applications
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8687823/
https://www.ncbi.nlm.nih.gov/pubmed/34938329
http://dx.doi.org/10.1155/2021/8016525
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