{"title":"智能手表在远程健康监测中的应用调查。","authors":"Christine E King, Majid Sarrafzadeh","doi":"10.1007/s41666-017-0012-7","DOIUrl":null,"url":null,"abstract":"<p><p>This systematic review classifies smartwatch-based healthcare applications in the literature according to their application and summarizes what has led to feasible systems. To this end, we conducted a systematic review of peer-reviewed smartwatch studies related to healthcare by searching PubMed, EBSCOHost, Springer, Elsevier, Pro-Quest, IEEE Xplore, and ACM Digital Library databases to find articles between 1998 and 2016. Inclusion criteria were: (1) a smartwatch was used, (2) the study was related to a healthcare application, (3) the study was a randomized controlled trial or pilot study, and (4) the study included human participant testing. Each article was evaluated in terms of its application, population type, setting, study size, study type, and features relevant to the smartwatch technology. After screening 1,119 articles, 27 articles were chosen that were directly related to healthcare. Classified applications included activity monitoring, chronic disease self-management, nursing or home-based care, and healthcare education. All studies were considered feasibility or usability studies, and had limited sample sizes. No randomized clinical trials were found. Also, most studies utilized Android-based smartwatches over Tizen, custom-built, or iOS- based smartwatches, and many relied on the use of the accelerometer and inertial sensors to elucidate physical activities. The results show that most research on smartwatches has been conducted only as feasibility studies for chronic disease self-management. Specifically, these applications targeted various disease conditions whose symptoms can easily be measured by inertial sensors, such as seizures or gait disturbances. In conclusion, although smartwatches show promise in healthcare, significant research on much larger populations is necessary to determine their acceptability and effectiveness in these applications.</p>","PeriodicalId":36444,"journal":{"name":"Journal of Healthcare Informatics Research","volume":"2 1-2","pages":"1-24"},"PeriodicalIF":5.9000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6051724/pdf/41666_2017_Article_12.pdf","citationCount":"0","resultStr":"{\"title\":\"A SURVEY OF SMARTWATCHES IN REMOTE HEALTH MONITORING.\",\"authors\":\"Christine E King, Majid Sarrafzadeh\",\"doi\":\"10.1007/s41666-017-0012-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This systematic review classifies smartwatch-based healthcare applications in the literature according to their application and summarizes what has led to feasible systems. To this end, we conducted a systematic review of peer-reviewed smartwatch studies related to healthcare by searching PubMed, EBSCOHost, Springer, Elsevier, Pro-Quest, IEEE Xplore, and ACM Digital Library databases to find articles between 1998 and 2016. Inclusion criteria were: (1) a smartwatch was used, (2) the study was related to a healthcare application, (3) the study was a randomized controlled trial or pilot study, and (4) the study included human participant testing. Each article was evaluated in terms of its application, population type, setting, study size, study type, and features relevant to the smartwatch technology. After screening 1,119 articles, 27 articles were chosen that were directly related to healthcare. Classified applications included activity monitoring, chronic disease self-management, nursing or home-based care, and healthcare education. All studies were considered feasibility or usability studies, and had limited sample sizes. No randomized clinical trials were found. Also, most studies utilized Android-based smartwatches over Tizen, custom-built, or iOS- based smartwatches, and many relied on the use of the accelerometer and inertial sensors to elucidate physical activities. The results show that most research on smartwatches has been conducted only as feasibility studies for chronic disease self-management. Specifically, these applications targeted various disease conditions whose symptoms can easily be measured by inertial sensors, such as seizures or gait disturbances. In conclusion, although smartwatches show promise in healthcare, significant research on much larger populations is necessary to determine their acceptability and effectiveness in these applications.</p>\",\"PeriodicalId\":36444,\"journal\":{\"name\":\"Journal of Healthcare Informatics Research\",\"volume\":\"2 1-2\",\"pages\":\"1-24\"},\"PeriodicalIF\":5.9000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6051724/pdf/41666_2017_Article_12.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Healthcare Informatics Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s41666-017-0012-7\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2017/12/18 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Healthcare Informatics Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s41666-017-0012-7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2017/12/18 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"Computer Science","Score":null,"Total":0}
A SURVEY OF SMARTWATCHES IN REMOTE HEALTH MONITORING.
This systematic review classifies smartwatch-based healthcare applications in the literature according to their application and summarizes what has led to feasible systems. To this end, we conducted a systematic review of peer-reviewed smartwatch studies related to healthcare by searching PubMed, EBSCOHost, Springer, Elsevier, Pro-Quest, IEEE Xplore, and ACM Digital Library databases to find articles between 1998 and 2016. Inclusion criteria were: (1) a smartwatch was used, (2) the study was related to a healthcare application, (3) the study was a randomized controlled trial or pilot study, and (4) the study included human participant testing. Each article was evaluated in terms of its application, population type, setting, study size, study type, and features relevant to the smartwatch technology. After screening 1,119 articles, 27 articles were chosen that were directly related to healthcare. Classified applications included activity monitoring, chronic disease self-management, nursing or home-based care, and healthcare education. All studies were considered feasibility or usability studies, and had limited sample sizes. No randomized clinical trials were found. Also, most studies utilized Android-based smartwatches over Tizen, custom-built, or iOS- based smartwatches, and many relied on the use of the accelerometer and inertial sensors to elucidate physical activities. The results show that most research on smartwatches has been conducted only as feasibility studies for chronic disease self-management. Specifically, these applications targeted various disease conditions whose symptoms can easily be measured by inertial sensors, such as seizures or gait disturbances. In conclusion, although smartwatches show promise in healthcare, significant research on much larger populations is necessary to determine their acceptability and effectiveness in these applications.
期刊介绍:
Journal of Healthcare Informatics Research serves as a publication venue for the innovative technical contributions highlighting analytics, systems, and human factors research in healthcare informatics.Journal of Healthcare Informatics Research is concerned with the application of computer science principles, information science principles, information technology, and communication technology to address problems in healthcare, and everyday wellness. Journal of Healthcare Informatics Research highlights the most cutting-edge technical contributions in computing-oriented healthcare informatics. The journal covers three major tracks: (1) analytics—focuses on data analytics, knowledge discovery, predictive modeling; (2) systems—focuses on building healthcare informatics systems (e.g., architecture, framework, design, engineering, and application); (3) human factors—focuses on understanding users or context, interface design, health behavior, and user studies of healthcare informatics applications. Topics include but are not limited to: · healthcare software architecture, framework, design, and engineering;· electronic health records· medical data mining· predictive modeling· medical information retrieval· medical natural language processing· healthcare information systems· smart health and connected health· social media analytics· mobile healthcare· medical signal processing· human factors in healthcare· usability studies in healthcare· user-interface design for medical devices and healthcare software· health service delivery· health games· security and privacy in healthcare· medical recommender system· healthcare workflow management· disease profiling and personalized treatment· visualization of medical data· intelligent medical devices and sensors· RFID solutions for healthcare· healthcare decision analytics and support systems· epidemiological surveillance systems and intervention modeling· consumer and clinician health information needs, seeking, sharing, and use· semantic Web, linked data, and ontology· collaboration technologies for healthcare· assistive and adaptive ubiquitous computing technologies· statistics and quality of medical data· healthcare delivery in developing countries· health systems modeling and simulation· computer-aided diagnosis