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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| Veröffentlicht in: | Computational intelligence and neuroscience 2021, Vol.2021 (1), p.8016525-8016525 |
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| creator | 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. |
| 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 (SpO2), 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 SpO2, and 0.13, 0.11, and 0.003, respectively, for body temperature. These results demonstrate the high accuracy and reliability of the proposed system. |
| doi_str_mv | 10.1155/2021/8016525 |
| format | Article |
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Abd ; El-Bahnasawy, Nirmeen A.</creator><contributor>Doulamis, Anastasios D. ; Anastasios D Doulamis</contributor><creatorcontrib>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. ; Doulamis, Anastasios D. ; Anastasios D Doulamis</creatorcontrib><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 (SpO2), 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 SpO2, and 0.13, 0.11, and 0.003, respectively, for body temperature. These results demonstrate the high accuracy and reliability of the proposed system.</description><identifier>ISSN: 1687-5265</identifier><identifier>EISSN: 1687-5273</identifier><identifier>DOI: 10.1155/2021/8016525</identifier><identifier>PMID: 34938329</identifier><language>eng</language><publisher>United States: Hindawi</publisher><subject>Algorithms ; Body temperature ; Chronic illnesses ; Cloud Computing ; Communication ; Communications systems ; Confidence intervals ; Coronaviruses ; COVID-19 ; Dashboards ; Disease transmission ; Emergency medical services ; Encryption ; Health care ; Heart beat ; Heart rate ; Hemoglobin ; Hospitals ; Humans ; Internet of Things ; Light emitting diodes ; Medical electronics ; Medical equipment ; Medical research ; Monitoring systems ; Oxygen content ; Oxygen Saturation ; Patients ; Personal health ; Physiological apparatus ; Physiology ; Pneumonia ; Privacy ; Pulse oximetry ; Reproducibility of Results ; Root-mean-square errors ; Sensors ; Signal monitoring ; Signal processing ; Telemedicine ; Vital signs</subject><ispartof>Computational intelligence and neuroscience, 2021, Vol.2021 (1), p.8016525-8016525</ispartof><rights>Copyright © 2021 Ali I. Siam et al.</rights><rights>COPYRIGHT 2021 John Wiley & Sons, Inc.</rights><rights>Copyright © 2021 Ali I. Siam et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0</rights><rights>Copyright © 2021 Ali I. Siam et al. 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c476t-852078964a520923ad4342ada5167f1d892b71742f0bfcd1284975ee6dcfc37e3</citedby><cites>FETCH-LOGICAL-c476t-852078964a520923ad4342ada5167f1d892b71742f0bfcd1284975ee6dcfc37e3</cites><orcidid>0000-0002-7242-5281 ; 0000-0003-0773-1597</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8687823/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8687823/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,4010,27900,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34938329$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Doulamis, Anastasios D.</contributor><contributor>Anastasios D Doulamis</contributor><creatorcontrib>Siam, Ali I.</creatorcontrib><creatorcontrib>Almaiah, Mohammed Amin</creatorcontrib><creatorcontrib>Al-Zahrani, Ali</creatorcontrib><creatorcontrib>Elazm, Atef Abou</creatorcontrib><creatorcontrib>El Banby, Ghada M.</creatorcontrib><creatorcontrib>El-Shafai, Walid</creatorcontrib><creatorcontrib>El-Samie, Fathi E. Abd</creatorcontrib><creatorcontrib>El-Bahnasawy, Nirmeen A.</creatorcontrib><title>Secure Health Monitoring Communication Systems Based on IoT and Cloud Computing for Medical Emergency Applications</title><title>Computational intelligence and neuroscience</title><addtitle>Comput Intell Neurosci</addtitle><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 (SpO2), 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 SpO2, and 0.13, 0.11, and 0.003, respectively, for body temperature. These results demonstrate the high accuracy and reliability of the proposed system.</description><subject>Algorithms</subject><subject>Body temperature</subject><subject>Chronic illnesses</subject><subject>Cloud Computing</subject><subject>Communication</subject><subject>Communications systems</subject><subject>Confidence intervals</subject><subject>Coronaviruses</subject><subject>COVID-19</subject><subject>Dashboards</subject><subject>Disease transmission</subject><subject>Emergency medical services</subject><subject>Encryption</subject><subject>Health care</subject><subject>Heart beat</subject><subject>Heart rate</subject><subject>Hemoglobin</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Internet of Things</subject><subject>Light emitting diodes</subject><subject>Medical electronics</subject><subject>Medical equipment</subject><subject>Medical research</subject><subject>Monitoring systems</subject><subject>Oxygen content</subject><subject>Oxygen Saturation</subject><subject>Patients</subject><subject>Personal health</subject><subject>Physiological apparatus</subject><subject>Physiology</subject><subject>Pneumonia</subject><subject>Privacy</subject><subject>Pulse oximetry</subject><subject>Reproducibility of Results</subject><subject>Root-mean-square errors</subject><subject>Sensors</subject><subject>Signal monitoring</subject><subject>Signal processing</subject><subject>Telemedicine</subject><subject>Vital signs</subject><issn>1687-5265</issn><issn>1687-5273</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNp9kUtv1DAUhSMEoqWwY40ssUGCoX7Ej2yQpqNCK7Vi0bK2PPbNjKvEDnYCmn9fhxlGwAJ54Sv7u8e-51TVa4I_EsL5OcWUnCtMBKf8SXVKhJILTiV7eqwFP6le5PyAMZcc0-fVCasbphhtTqt0B3ZKgK7AdOMW3cbgx5h82KBV7PspeGtGHwO62-UR-owuTAaHysF1vEcmOLTq4uRmeJjGua2NCd2CK30duuwhbSDYHVoOQ3eQyi-rZ63pMrw67GfVt8-X96urxc3XL9er5c3C1lKMC8UplqoRtSlFQ5lxNaupcYYTIVviVEPXksiatnjdWkeoqhvJAYSzrWUS2Fn1aa87TOsenIUwJtPpIfnepJ2Oxuu_b4Lf6k38oVWxTVFWBN4dBFL8PkEede-zha4zAeKUNRWkeFhLggv69h_0IU4plPF-UY2gvBh-pDamA-1DG8u7dhbVS9GUpWomC_VhT9kUc07QHr9MsJ4j13Pk-hB5wd_8OeYR_p1xAd7vga0Pzvz0_5d7BFnhsto</recordid><startdate>2021</startdate><enddate>2021</enddate><creator>Siam, Ali I.</creator><creator>Almaiah, Mohammed Amin</creator><creator>Al-Zahrani, Ali</creator><creator>Elazm, Atef Abou</creator><creator>El Banby, Ghada M.</creator><creator>El-Shafai, Walid</creator><creator>El-Samie, Fathi E. 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Abd</au><au>El-Bahnasawy, Nirmeen A.</au><au>Doulamis, Anastasios D.</au><au>Anastasios D Doulamis</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Secure Health Monitoring Communication Systems Based on IoT and Cloud Computing for Medical Emergency Applications</atitle><jtitle>Computational intelligence and neuroscience</jtitle><addtitle>Comput Intell Neurosci</addtitle><date>2021</date><risdate>2021</risdate><volume>2021</volume><issue>1</issue><spage>8016525</spage><epage>8016525</epage><pages>8016525-8016525</pages><issn>1687-5265</issn><eissn>1687-5273</eissn><abstract>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 (SpO2), 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 SpO2, and 0.13, 0.11, and 0.003, respectively, for body temperature. These results demonstrate the high accuracy and reliability of the proposed system.</abstract><cop>United States</cop><pub>Hindawi</pub><pmid>34938329</pmid><doi>10.1155/2021/8016525</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0002-7242-5281</orcidid><orcidid>https://orcid.org/0000-0003-0773-1597</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | Computational intelligence and neuroscience, 2021, Vol.2021 (1), p.8016525-8016525 |
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| source | MEDLINE; Wiley Online Library Open Access; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; PubMed Central; Alma/SFX Local Collection; PubMed Central Open Access |
| subjects | Algorithms Body temperature Chronic illnesses Cloud Computing Communication Communications systems Confidence intervals Coronaviruses COVID-19 Dashboards Disease transmission Emergency medical services Encryption Health care Heart beat Heart rate Hemoglobin Hospitals Humans Internet of Things Light emitting diodes Medical electronics Medical equipment Medical research Monitoring systems Oxygen content Oxygen Saturation Patients Personal health Physiological apparatus Physiology Pneumonia Privacy Pulse oximetry Reproducibility of Results Root-mean-square errors Sensors Signal monitoring Signal processing Telemedicine Vital signs |
| title | Secure Health Monitoring Communication Systems Based on IoT and Cloud Computing for Medical Emergency Applications |
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