{"title":"Virtual Healthcare Technologies and Consultation Systems, Smart Operating Rooms, and Remote Sensing Data Fusion Algorithms in the Medical Metaverse","authors":"","doi":"10.22381/ajmr9220227","DOIUrl":"https://doi.org/10.22381/ajmr9220227","url":null,"abstract":"","PeriodicalId":91446,"journal":{"name":"American journal of medical research (New York, N.Y.)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68354099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Resting Motor Threshold (RMT) during “Preservation” Transcranial Magnetic Stimulation (TMS)","authors":"","doi":"10.22381/ajmr9120221","DOIUrl":"https://doi.org/10.22381/ajmr9120221","url":null,"abstract":"","PeriodicalId":91446,"journal":{"name":"American journal of medical research (New York, N.Y.)","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68352826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Barbara Cug Juraj Michalikova Katarina Frajtova Crowell
Keywords: Internet of Medical Things;diagnostic algorithm;COVID-19 1.Introduction The purpose of our systematic review is to examine the recently published literature on COVID-19 detection and treatment and integrate the insights it configures on smart wearable Internet of Medical Things technologies, artificial intelligence-based diagnostic algorithms, and real-time healthcare monitoring systems. The manuscript is organized as following: theoretical overview (section 2), methodology (section 3), networked sensors, wearable devices, and smart clinical systems (section 4), real-time healthcare monitoring systems and processing algorithms in Internet of Medical Things (section 5), smart personalized healthcare applications and services (section 6), discussion (section 7), synopsis of the main research outcomes (section 8), conclusions (section 9), limitations, implications, and further directions of research (section 10). 4.Networked Sensors, Wearable Devices, and Smart Clinical Systems Internet of Medical Things is pivotal in heterogeneous clinical trials, disease monitoring, and healthcare procedures (Gul et al., 2021;Maitra et al., 2021;Scrugli et al., 2022) through wireless data collection, analysis, and sharing. Specialized machine learning and predictive algorithms can be pivotal in preventive screenings, monitoring vital signs and life-threatening conditions, and supporting clinical judgment in COVID-19 early recognition and treatment by analyzing patient records and clinical data.
{"title":"Smart Wearable Internet of Medical Things Technologies, Artificial Intelligence-based Diagnostic Algorithms, and Real-Time Healthcare Monitoring Systems in COVID-19 Detection and Treatment","authors":"Barbara Cug Juraj Michalikova Katarina Frajtova Crowell","doi":"10.22381/ajmr9120222","DOIUrl":"https://doi.org/10.22381/ajmr9120222","url":null,"abstract":"Keywords: Internet of Medical Things;diagnostic algorithm;COVID-19 1.Introduction The purpose of our systematic review is to examine the recently published literature on COVID-19 detection and treatment and integrate the insights it configures on smart wearable Internet of Medical Things technologies, artificial intelligence-based diagnostic algorithms, and real-time healthcare monitoring systems. The manuscript is organized as following: theoretical overview (section 2), methodology (section 3), networked sensors, wearable devices, and smart clinical systems (section 4), real-time healthcare monitoring systems and processing algorithms in Internet of Medical Things (section 5), smart personalized healthcare applications and services (section 6), discussion (section 7), synopsis of the main research outcomes (section 8), conclusions (section 9), limitations, implications, and further directions of research (section 10). 4.Networked Sensors, Wearable Devices, and Smart Clinical Systems Internet of Medical Things is pivotal in heterogeneous clinical trials, disease monitoring, and healthcare procedures (Gul et al., 2021;Maitra et al., 2021;Scrugli et al., 2022) through wireless data collection, analysis, and sharing. Specialized machine learning and predictive algorithms can be pivotal in preventive screenings, monitoring vital signs and life-threatening conditions, and supporting clinical judgment in COVID-19 early recognition and treatment by analyzing patient records and clinical data.","PeriodicalId":91446,"journal":{"name":"American journal of medical research (New York, N.Y.)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68352937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Telehealth can be used to decrease healthcare worker exposure and personal protective equipment donning, doffing, and conservation, while caring for COVID-19 patients and providing virtual urgent care screenings. The manuscript is organized as following: theoretical overview (section 2), methodology (section 3), interconnected and heterogeneous networks in patient diagnosis, monitoring, and treatment (section 4), monitoring systems and wearable sensors integrated in Internet of Medical Things and smart healthcare (section 5), networked wearable devices, machine learning algorithms, and Internet of Medical Things (section 6), discussion (section 7), synopsis of the main research outcomes (section 8), conclusions (section 9), limitations, implications, and further directions of research (section 10). 4.Interconnected and Heterogeneous Networks in Patient Diagnosis, Monitoring, and Treatment Smart healthcare leverages Internet of Medical Things, wireless communication technologies, medical sensors, wearable devices, and machine learning algorithms (Calvillo-Arbizu et al., 2021;Chang et al., 2022;Muhammad et al., 2021) to inspect patient data. Telehealth can be used to decrease healthcare worker exposure and personal protective equipment donning, doffing, and conservation, while caring for COVID-19 patients and providing virtual urgent care screenings. Internet of Medical Things articulates appropriate and inexpensive manners for healthcare delivery by integrating remote access in patient physiological data collection while harnessing machine learning techniques in diagnosis assistance.
远程医疗可用于减少卫生保健工作者的接触和个人防护装备的穿戴、脱下和保护，同时照顾COVID-19患者并提供虚拟紧急护理筛查。全文组织如下:理论概述(第2节)、方法(第3节)、患者诊断、监测和治疗中的互联和异构网络(第4节)、医疗物联网和智能医疗中集成的监测系统和可穿戴传感器(第5节)、联网可穿戴设备、机器学习算法和医疗物联网(第6节)、讨论(第7节)、主要研究成果概述(第8节)、结论(第9节)、局限性、影响和进一步的研究方向(第10节)。4.智能医疗利用医疗物联网、无线通信技术、医疗传感器、可穿戴设备和机器学习算法(Calvillo-Arbizu et al.， 2021;Chang et al.， 2022;Muhammad et al.， 2021)检查患者数据。远程医疗可用于减少卫生保健工作者的接触和个人防护装备的穿戴、脱下和保护，同时照顾COVID-19患者并提供虚拟紧急护理筛查。医疗物联网通过在患者生理数据收集中集成远程访问，同时在诊断辅助中利用机器学习技术，阐明了适当且廉价的医疗保健提供方式。
{"title":"Networked Wearable Devices, Machine Learning-based Real-Time Data Sensing and Processing, and Internet of Medical Things in COVID-19 Diagnosis, Prognosis, and Treatment","authors":"R. Balica","doi":"10.22381/ajmr9120223","DOIUrl":"https://doi.org/10.22381/ajmr9120223","url":null,"abstract":"Telehealth can be used to decrease healthcare worker exposure and personal protective equipment donning, doffing, and conservation, while caring for COVID-19 patients and providing virtual urgent care screenings. The manuscript is organized as following: theoretical overview (section 2), methodology (section 3), interconnected and heterogeneous networks in patient diagnosis, monitoring, and treatment (section 4), monitoring systems and wearable sensors integrated in Internet of Medical Things and smart healthcare (section 5), networked wearable devices, machine learning algorithms, and Internet of Medical Things (section 6), discussion (section 7), synopsis of the main research outcomes (section 8), conclusions (section 9), limitations, implications, and further directions of research (section 10). 4.Interconnected and Heterogeneous Networks in Patient Diagnosis, Monitoring, and Treatment Smart healthcare leverages Internet of Medical Things, wireless communication technologies, medical sensors, wearable devices, and machine learning algorithms (Calvillo-Arbizu et al., 2021;Chang et al., 2022;Muhammad et al., 2021) to inspect patient data. Telehealth can be used to decrease healthcare worker exposure and personal protective equipment donning, doffing, and conservation, while caring for COVID-19 patients and providing virtual urgent care screenings. Internet of Medical Things articulates appropriate and inexpensive manners for healthcare delivery by integrating remote access in patient physiological data collection while harnessing machine learning techniques in diagnosis assistance.","PeriodicalId":91446,"journal":{"name":"American journal of medical research (New York, N.Y.)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68352991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Keywords: Internet of Things;wearable medical sensor device;COVID-19 1.Introduction The purpose of my systematic review is to examine the recently published literature on COVID-19 patient screening, diagnosis, monitoring, and treatment, and integrate the insights it configures on wearable medical sensor devices, machine and deep learning algorithms, and Internet of Things-based healthcare systems. The identified gaps advance how smart healthcare services are essential in remote patient monitoring through medical data storage, transfer, sharing, processing, collection, and analysis. The manuscript is organized as following: theoretical overview (section 2), methodology (section 3), machine learning algorithms in COVID-19 patient screening, diagnosis, monitoring, tracking, and treatment (section 4), wireless wearable healthcare networks and smart mobile devices in Internet of Medical Things (section 5), smart healthcare services in remote patient monitoring (section 6), discussion (section 7), synopsis of the main research outcomes (section 8), conclusions (section 9), limitations, implications, and further directions of research (section 10). Taking into account the physiological features of people, distinct treatment replications through medical sensor devices can be performed to evaluate the health risk and establish exemplary medical procedures.
{"title":"Wearable Medical Sensor Devices, Machine and Deep Learning Algorithms, and Internet of Things-based Healthcare Systems in COVID-19 Patient Screening, Diagnosis, Monitoring, and Treatment","authors":"Thomas Jenkins","doi":"10.22381/ajmr9120224","DOIUrl":"https://doi.org/10.22381/ajmr9120224","url":null,"abstract":"Keywords: Internet of Things;wearable medical sensor device;COVID-19 1.Introduction The purpose of my systematic review is to examine the recently published literature on COVID-19 patient screening, diagnosis, monitoring, and treatment, and integrate the insights it configures on wearable medical sensor devices, machine and deep learning algorithms, and Internet of Things-based healthcare systems. The identified gaps advance how smart healthcare services are essential in remote patient monitoring through medical data storage, transfer, sharing, processing, collection, and analysis. The manuscript is organized as following: theoretical overview (section 2), methodology (section 3), machine learning algorithms in COVID-19 patient screening, diagnosis, monitoring, tracking, and treatment (section 4), wireless wearable healthcare networks and smart mobile devices in Internet of Medical Things (section 5), smart healthcare services in remote patient monitoring (section 6), discussion (section 7), synopsis of the main research outcomes (section 8), conclusions (section 9), limitations, implications, and further directions of research (section 10). Taking into account the physiological features of people, distinct treatment replications through medical sensor devices can be performed to evaluate the health risk and establish exemplary medical procedures.","PeriodicalId":91446,"journal":{"name":"American journal of medical research (New York, N.Y.)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68353099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Based on an in-depth survey of the literature, the purpose of the paper is to explore remote patient monitoring systems, wearable Internet of Medical Things sensor devices, and deep learning-based computer vision algorithms in COVID-19 screening, detection, diagnosis, and treatment. Keywords: remote patient monitoring;Internet of Medical Things;COVID-19 1.Introduction The purpose of my systematic review is to examine the recently published literature on COVID-19 screening, detection, diagnosis, and treatment, and integrate the insights it configures on remote patient monitoring systems, wearable Internet of Medical Things sensor devices, and deep learning-based computer vision algorithms. The manuscript is organized as following: theoretical overview (section 2), methodology (section 3), machine and deep learning-based COVID-19 diagnostic and predicting tools and applications (section 4), wearable Internet of Medical Things devices and sensing technologies (section 5), machine learning algorithms, implantable medical devices, wireless body networks, and computer vision (section 6), discussion (section 7), synopsis of the main research outcomes (section 8), conclusions (section 9), limitations, implications, and further directions of research (section 10). (Table 4) 6.Machine Learning Algorithms, Implantable Medical Devices, Wireless Body Networks, and Computer Vision Internet of Medical Things can be instrumental in COVID-19 prevention and detection accuracy (Douglas Miller and Brown, 2019;Kong et al., 2021;Li et al., 2021;Rhayem et al., 2021) through data collection and processing, healthcare monitoring systems, and intervention measures.
{"title":"Remote Patient Monitoring Systems, Wearable Internet of Medical Things Sensor Devices, and Deep Learning-based Computer Vision Algorithms in COVID-19 Screening, Detection, Diagnosis, and Treatment","authors":"Adela-Claudia Cuţitoi","doi":"10.22381/ajmr9120229","DOIUrl":"https://doi.org/10.22381/ajmr9120229","url":null,"abstract":"Based on an in-depth survey of the literature, the purpose of the paper is to explore remote patient monitoring systems, wearable Internet of Medical Things sensor devices, and deep learning-based computer vision algorithms in COVID-19 screening, detection, diagnosis, and treatment. Keywords: remote patient monitoring;Internet of Medical Things;COVID-19 1.Introduction The purpose of my systematic review is to examine the recently published literature on COVID-19 screening, detection, diagnosis, and treatment, and integrate the insights it configures on remote patient monitoring systems, wearable Internet of Medical Things sensor devices, and deep learning-based computer vision algorithms. The manuscript is organized as following: theoretical overview (section 2), methodology (section 3), machine and deep learning-based COVID-19 diagnostic and predicting tools and applications (section 4), wearable Internet of Medical Things devices and sensing technologies (section 5), machine learning algorithms, implantable medical devices, wireless body networks, and computer vision (section 6), discussion (section 7), synopsis of the main research outcomes (section 8), conclusions (section 9), limitations, implications, and further directions of research (section 10). (Table 4) 6.Machine Learning Algorithms, Implantable Medical Devices, Wireless Body Networks, and Computer Vision Internet of Medical Things can be instrumental in COVID-19 prevention and detection accuracy (Douglas Miller and Brown, 2019;Kong et al., 2021;Li et al., 2021;Rhayem et al., 2021) through data collection and processing, healthcare monitoring systems, and intervention measures.","PeriodicalId":91446,"journal":{"name":"American journal of medical research (New York, N.Y.)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68353138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Keywords: Internet of Things;machine and deep learning algorithm;COVID-19 1.Introduction The purpose of our systematic review is to examine the recently published literature on COVID-19 prevention, testing, detection, and treatment, and integrate the insights it configures on machine and deep learning algorithms, computer vision technologies, and Internet of Things-based healthcare monitoring systems. The manuscript is organized as following: theoretical overview (section 2), methodology (section 3), COVID19 detection and diagnostic tools (section 4), machine learning techniques, healthcare sensor devices, and computer vision (section 5), machine learning algorithms and Internet of Things-based monitoring systems (section 6), discussion (section 7), synopsis of the main research outcomes (section 8), conclusions (section 9), limitations, implications, and further directions of research (section 10). (Table 3) 5.Machine Learning Techniques, Healthcare Sensor Devices, and Computer Vision Internet of Things-based healthcare monitoring systems are pivotal in accurate and suitable patient treatment (Jain et al., 2021;Li et al., 2021;Rhayem et al., 2021;Zhang et al., 2021a) by integrating medical wearable sensors, actuators, and networked devices. (Table 4) 6.Machine Learning Algorithms and Internet of Things-based Monitoring Systems Internet of Medical Things devices and wearables can be pivotal in contact tracing, early diagnosis, and symptom tracking (Khowaja et al., 2021;Mehrdad et al., 2021;Tai et al., 2021) by use of machine learning techniques, neural network architectures, and data fusion.
{"title":"Machine and Deep Learning Algorithms, Computer Vision Technologies, and Internet of Things-based Healthcare Monitoring Systems in COVID-19 Prevention, Testing, Detection, and Treatment","authors":"Katarína Zvaríková","doi":"10.22381/ajmr91202210","DOIUrl":"https://doi.org/10.22381/ajmr91202210","url":null,"abstract":"Keywords: Internet of Things;machine and deep learning algorithm;COVID-19 1.Introduction The purpose of our systematic review is to examine the recently published literature on COVID-19 prevention, testing, detection, and treatment, and integrate the insights it configures on machine and deep learning algorithms, computer vision technologies, and Internet of Things-based healthcare monitoring systems. The manuscript is organized as following: theoretical overview (section 2), methodology (section 3), COVID19 detection and diagnostic tools (section 4), machine learning techniques, healthcare sensor devices, and computer vision (section 5), machine learning algorithms and Internet of Things-based monitoring systems (section 6), discussion (section 7), synopsis of the main research outcomes (section 8), conclusions (section 9), limitations, implications, and further directions of research (section 10). (Table 3) 5.Machine Learning Techniques, Healthcare Sensor Devices, and Computer Vision Internet of Things-based healthcare monitoring systems are pivotal in accurate and suitable patient treatment (Jain et al., 2021;Li et al., 2021;Rhayem et al., 2021;Zhang et al., 2021a) by integrating medical wearable sensors, actuators, and networked devices. (Table 4) 6.Machine Learning Algorithms and Internet of Things-based Monitoring Systems Internet of Medical Things devices and wearables can be pivotal in contact tracing, early diagnosis, and symptom tracking (Khowaja et al., 2021;Mehrdad et al., 2021;Tai et al., 2021) by use of machine learning techniques, neural network architectures, and data fusion.","PeriodicalId":91446,"journal":{"name":"American journal of medical research (New York, N.Y.)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68352853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Wearable Healthcare Monitoring Devices, 3D Medical Imaging Data, and Virtualized Care Systems in the Decentralized and Interconnected Metaverse","authors":"","doi":"10.22381/ajmr9220229","DOIUrl":"https://doi.org/10.22381/ajmr9220229","url":null,"abstract":"","PeriodicalId":91446,"journal":{"name":"American journal of medical research (New York, N.Y.)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68353783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Immersive Virtual Reality Technologies, 3D Data Modeling and Simulation Tools, and Artificial Intelligence-based Diagnostic Algorithms on Metaverse Medical Platforms","authors":"","doi":"10.22381/ajmr9220224","DOIUrl":"https://doi.org/10.22381/ajmr9220224","url":null,"abstract":"","PeriodicalId":91446,"journal":{"name":"American journal of medical research (New York, N.Y.)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68353160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Keywords: remote patient monitoring;body sensor network;COVID-19 1.Introduction The purpose of our systematic review is to examine the recently published literature on COVID-19 remote patient monitoring and integrate the insights it configures on machine and deep learning techniques, body sensor networks, and Internet of Things-based smart healthcare systems. The manuscript is organized as following: theoretical overview (section 2), methodology (section 3), COVID-19 physiological sensor data measurement and healthcare monitoring (section 4), COVID-19 detection and monitoring tools (section 5), Internet of Medical Things-enabled remote healthcare services (section 6), discussion (section 7), synopsis of the main research outcomes (section 8), conclusions (section 9), limitations, implications, and further directions of research (section 10). Internet of Things-enabled wearable medical devices and biological sensors transfer relevant data to optimize the performance of medical personnel, integrating monitoring and prevention, and treatment strategies. Medical data exchange can result in enhanced healthcare quality and systems, optimizing the feedback time in emergency situations, and precise detection and control of COVID-19.
{"title":"Machine and Deep Learning Techniques, Body Sensor Networks, and Internet of Things-based Smart Healthcare Systems in COVID-19 Remote Patient Monitoring","authors":"Diana Michalkova Lucia Machova Veronika Stone","doi":"10.22381/ajmr9120227","DOIUrl":"https://doi.org/10.22381/ajmr9120227","url":null,"abstract":"Keywords: remote patient monitoring;body sensor network;COVID-19 1.Introduction The purpose of our systematic review is to examine the recently published literature on COVID-19 remote patient monitoring and integrate the insights it configures on machine and deep learning techniques, body sensor networks, and Internet of Things-based smart healthcare systems. The manuscript is organized as following: theoretical overview (section 2), methodology (section 3), COVID-19 physiological sensor data measurement and healthcare monitoring (section 4), COVID-19 detection and monitoring tools (section 5), Internet of Medical Things-enabled remote healthcare services (section 6), discussion (section 7), synopsis of the main research outcomes (section 8), conclusions (section 9), limitations, implications, and further directions of research (section 10). Internet of Things-enabled wearable medical devices and biological sensors transfer relevant data to optimize the performance of medical personnel, integrating monitoring and prevention, and treatment strategies. Medical data exchange can result in enhanced healthcare quality and systems, optimizing the feedback time in emergency situations, and precise detection and control of COVID-19.","PeriodicalId":91446,"journal":{"name":"American journal of medical research (New York, N.Y.)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68353438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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