可视化可穿戴医疗器械研究趋势:基于文献计量学的共现网络分析

IF 0.3 Q3 MEDICINE, GENERAL & INTERNAL
Bitan Misra, Nilanjana Dutta Roy, Nilanjan Dey, R. Sherratt
{"title":"可视化可穿戴医疗器械研究趋势:基于文献计量学的共现网络分析","authors":"Bitan Misra, Nilanjana Dutta Roy, Nilanjan Dey, R. Sherratt","doi":"10.21802/gmj.2023.3.2","DOIUrl":null,"url":null,"abstract":"Background. One of the most crucial aspects of someone’s life is health. Therefore, individuals should be conscious about keeping themselves healthy by regular monitoring their health, which can be done with the help of modern medical technologies. Wearable medical devices using wearable sensors are the popular names of emerging technologies in the modern healthcare domain. \nAim. This work presents the results of a systematic investigation of extensive research that has occurred for the last two decades in these research streams to provide a comprehensive mapping and temporal distribution of wireless medical device research. \nMethods. This study presents a relationship between the bibliographic items, their quality, and the quantity representing the most effective research topics on wearable medical devices. The analysis is performed using two useful parameters, namely a bibliometric network and a co-occurrence matrix. Data collection, data standardization, data mapping, and result analysis are the steps involved in the bibliometric analysis technique. In this study, VOSviewer software for bibliometric analysis is applied to the Scopus database. \nResults. By analysing bibliometric indicators from the Scopus database and using VOSviewer, we represent their distribution in countries, institutions, top researchers, and top journals. Furthermore, we analyse the co-citation of cited authors and the co-occurrence of keywords. The outcomes of the clustering and keyword analysis indicate that the research domain primarily focuses on the Internet of Things, machine learning, wearable sensors, mobile health, electrocardiogram, etc. \nConclusions. Statistical investigation in association with the visual exploration presented in this article provides more substantial information than either of them used separately. In the future, this article can illuminate researchers and practitioners to develop a different theory to look at the factors that influence predictability in the research domain of wearable medical devices.","PeriodicalId":12537,"journal":{"name":"Galician Medical Journal","volume":" ","pages":""},"PeriodicalIF":0.3000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Visualizing Wearable Medical Device Research Trends: A Co-occurrence Network-Based Bibliometric Analysis\",\"authors\":\"Bitan Misra, Nilanjana Dutta Roy, Nilanjan Dey, R. Sherratt\",\"doi\":\"10.21802/gmj.2023.3.2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background. One of the most crucial aspects of someone’s life is health. Therefore, individuals should be conscious about keeping themselves healthy by regular monitoring their health, which can be done with the help of modern medical technologies. Wearable medical devices using wearable sensors are the popular names of emerging technologies in the modern healthcare domain. \\nAim. This work presents the results of a systematic investigation of extensive research that has occurred for the last two decades in these research streams to provide a comprehensive mapping and temporal distribution of wireless medical device research. \\nMethods. This study presents a relationship between the bibliographic items, their quality, and the quantity representing the most effective research topics on wearable medical devices. The analysis is performed using two useful parameters, namely a bibliometric network and a co-occurrence matrix. Data collection, data standardization, data mapping, and result analysis are the steps involved in the bibliometric analysis technique. In this study, VOSviewer software for bibliometric analysis is applied to the Scopus database. \\nResults. By analysing bibliometric indicators from the Scopus database and using VOSviewer, we represent their distribution in countries, institutions, top researchers, and top journals. Furthermore, we analyse the co-citation of cited authors and the co-occurrence of keywords. The outcomes of the clustering and keyword analysis indicate that the research domain primarily focuses on the Internet of Things, machine learning, wearable sensors, mobile health, electrocardiogram, etc. \\nConclusions. Statistical investigation in association with the visual exploration presented in this article provides more substantial information than either of them used separately. In the future, this article can illuminate researchers and practitioners to develop a different theory to look at the factors that influence predictability in the research domain of wearable medical devices.\",\"PeriodicalId\":12537,\"journal\":{\"name\":\"Galician Medical Journal\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2023-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Galician Medical Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21802/gmj.2023.3.2\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MEDICINE, GENERAL & INTERNAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Galician Medical Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21802/gmj.2023.3.2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0

摘要

背景健康是一个人生活中最重要的方面之一。因此,个人应该有意识地通过定期监测自己的健康状况来保持自己的健康,这可以在现代医疗技术的帮助下实现。使用可穿戴传感器的可穿戴医疗设备是现代医疗领域新兴技术的流行名称。目标这项工作展示了过去二十年来在这些研究流中进行的广泛研究的系统调查结果,以提供无线医疗设备研究的全面映射和时间分布。方法。本研究介绍了可穿戴医疗设备最有效研究主题的目录项目、质量和数量之间的关系。使用两个有用的参数进行分析,即文献计量网络和共现矩阵。数据收集、数据标准化、数据映射和结果分析是文献计量分析技术中涉及的步骤。本研究将VOSviewer文献计量分析软件应用于Scopus数据库。后果通过分析Scopus数据库中的文献计量指标并使用VOSviewer,我们代表了它们在国家、机构、顶级研究人员和顶级期刊中的分布。此外,我们还分析了被引作者的共引和关键词的共现。聚类和关键词分析结果表明,该研究领域主要集中在物联网、机器学习、可穿戴传感器、移动健康、心电图等方面。本文中提出的与视觉探索相关的统计调查提供了比单独使用的任何一种都更实质性的信息。未来,本文可以启发研究人员和从业者开发一种不同的理论,来研究影响可穿戴医疗设备研究领域可预测性的因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Visualizing Wearable Medical Device Research Trends: A Co-occurrence Network-Based Bibliometric Analysis
Background. One of the most crucial aspects of someone’s life is health. Therefore, individuals should be conscious about keeping themselves healthy by regular monitoring their health, which can be done with the help of modern medical technologies. Wearable medical devices using wearable sensors are the popular names of emerging technologies in the modern healthcare domain. Aim. This work presents the results of a systematic investigation of extensive research that has occurred for the last two decades in these research streams to provide a comprehensive mapping and temporal distribution of wireless medical device research. Methods. This study presents a relationship between the bibliographic items, their quality, and the quantity representing the most effective research topics on wearable medical devices. The analysis is performed using two useful parameters, namely a bibliometric network and a co-occurrence matrix. Data collection, data standardization, data mapping, and result analysis are the steps involved in the bibliometric analysis technique. In this study, VOSviewer software for bibliometric analysis is applied to the Scopus database. Results. By analysing bibliometric indicators from the Scopus database and using VOSviewer, we represent their distribution in countries, institutions, top researchers, and top journals. Furthermore, we analyse the co-citation of cited authors and the co-occurrence of keywords. The outcomes of the clustering and keyword analysis indicate that the research domain primarily focuses on the Internet of Things, machine learning, wearable sensors, mobile health, electrocardiogram, etc. Conclusions. Statistical investigation in association with the visual exploration presented in this article provides more substantial information than either of them used separately. In the future, this article can illuminate researchers and practitioners to develop a different theory to look at the factors that influence predictability in the research domain of wearable medical devices.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
审稿时长
6 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信