Machine and Deep Learning Techniques, Body Sensor Networks, and Internet of Things-based Smart Healthcare Systems in COVID-19 Remote Patient Monitoring
{"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":null,"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":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"American journal of medical research (New York, N.Y.)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22381/ajmr9120227","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
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.