Department of Dentistry and Oral Surgery, Unit of Sensory and Locomotor Medicine, Division of Medicine, Faculty of Medical Sciences, University of Fukui, 23-3 Matsuokashimoaizuki, Eiheiji-cho, Yoshida-gun, 910-1193, Fukui, Japan.
Syst Rev. 2022 Jan 6;11(1):7. doi: 10.1186/s13643-021-01879-z.
Artificial intelligence is useful for building objective and rapid personal identification systems. It is important to research and develop personal identification methods as social and institutional infrastructure. A critical consideration during the coronavirus disease 2019 pandemic is that there is no contact between the subjects and personal identification systems. The aim of this study was to organize the recent 5-year development of contactless personal identification methods that use artificial intelligence.
This study used a scoping review approach to map the progression of contactless personal identification systems using artificial intelligence over the past 5 years. An electronic systematic literature search was conducted using the PubMed, Web of Science, Cochrane Library, CINAHL, and IEEE Xplore databases. Studies published between January 2016 and December 2020 were included in the study.
By performing an electronic literature search, 83 articles were extracted. Based on the PRISMA flow diagram, 8 eligible articles were included in this study. These eligible articles were divided based on the analysis targets as follows: (1) face and/or body, (2) eye, and (3) forearm and/or hand. Artificial intelligence, including convolutional neural networks, contributed to the progress of research on contactless personal identification methods.
This study clarified that contactless personal identification methods using artificial intelligence have progressed and that they have used information obtained from the face and/or body, eyes, and forearm and/or hand.
人工智能在构建客观、快速的个人身份识别系统方面很有用。研究和开发个人身份识别方法作为社会和机构基础设施非常重要。在 2019 年冠状病毒病大流行期间，一个关键的考虑因素是主体与个人身份识别系统之间没有接触。本研究旨在组织过去 5 年来使用人工智能的非接触式个人身份识别方法的最新进展。
本研究采用范围综述方法，绘制了过去 5 年使用人工智能的非接触式个人身份识别系统的进展情况。使用 PubMed、Web of Science、Cochrane Library、CINAHL 和 IEEE Xplore 数据库进行电子系统文献检索。研究纳入了 2016 年 1 月至 2020 年 12 月期间发表的研究。
通过电子文献检索，提取了 83 篇文章。根据 PRISMA 流程图，本研究纳入了 8 篇合格的文章。这些合格的文章根据分析目标进行了分类，如下所示：（1）面部和/或身体，（2）眼睛，（3）前臂和/或手。人工智能，包括卷积神经网络，推动了非接触式个人身份识别方法的研究进展。
本研究表明，使用人工智能的非接触式个人身份识别方法已经取得了进展，并且已经使用了从面部和/或身体、眼睛以及前臂和/或手部获取的信息。
