Department of Clinical Technology, Faculty of Mechanical, Maritime and Materials Engineering (3Me), Delft University of Technology, Mekelweg 2, 2628 CD Delft, The Netherlands.
Department of Radiology, Albinusdreef 2, NL-2333 ZA Leiden, The Netherlands.
Sensors (Basel). 2020 Jul 15;20(14):3937. doi: 10.3390/s20143937.
In the critical setting of a trauma team activation, team composition is crucial information that should be accessible at a glance. This calls for a technological solution, which are widely available, that allows access to the whereabouts of personnel. This diversity presents decision makers and users with many choices and considerations. The aim of this review is to give a comprehensive overview of available real-time person identification techniques and their respective characteristics. A systematic literature review was performed to create an overview of identification techniques that have been tested in medical settings or already have been implemented in clinical practice. These techniques have been investigated on a total of seven characteristics: costs, usability, accuracy, response time, hygiene, privacy, and user safety. The search was performed on 11 May 2020 in PubMed and the Web of Science Core Collection. PubMed and Web of Science yielded a total n = 265 and n = 228 records, respectively. The review process resulted in n = 23 included records. A total of seven techniques were identified: (a) active and (b) passive Radio-Frequency Identification (RFID) based systems, (c) fingerprint, (d) iris, and (e) facial identification systems and infrared (IR) (f) and ultrasound (US) (g) based systems. Active RFID was largely documented in the included literature. Only a few could be found about the passive systems. Biometric (c, d, and e) technologies were described in a variety of applications. IR and US techniques appeared to be a niche, as they were only spoken of in few (n = 3) studies.
在创伤团队激活的关键环境中,团队组成是一眼就能看到的关键信息。这需要一个技术解决方案,目前有许多这样的解决方案,可以访问人员的位置。这种多样性为决策者和用户提供了许多选择和考虑因素。本综述的目的是全面概述可用的实时人员识别技术及其各自的特点。进行了系统的文献回顾,以概述已在医疗环境中进行测试或已在临床实践中实施的识别技术。这些技术在总共七个特征方面进行了研究:成本、可用性、准确性、响应时间、卫生、隐私和用户安全。搜索于 2020 年 5 月 11 日在 PubMed 和 Web of Science Core Collection 上进行。PubMed 和 Web of Science 分别产生了 n = 265 和 n = 228 条记录。审查过程导致 n = 23 条记录被纳入。总共确定了七种技术:(a)主动和(b)被动射频识别 (RFID) 系统、(c)指纹、(d)虹膜和(e)面部识别系统以及红外 (IR) (f)和超声 (US) (g)基于系统。主动 RFID 在纳入的文献中得到了广泛的记录。只有少数被动系统的相关信息被找到。生物识别技术(c、d 和 e)在各种应用中都有描述。IR 和 US 技术似乎是一个利基市场,因为只有少数(n = 3)研究提到了它们。