Self-powered wearable Internet of Things sensors for human-machine interfaces: A systematic literature review and science mapping analysis

Abstract

With the advent of Internet of Things (IoT), self-powered wearable sensors have seen broad applications across various human-machine interface (HMI) domains, including manufacturing, healthcare, biomedicine, and automobile. However, these sensors have not yet been systematically and scientifically reviewed within the construction industry. This study aims to conduct both a systematic literature review and a science mapping analysis of self-powered wearable IoT sensors for HMI to uncover mainstream research topics, research gaps, and future research directions. Using PRISMA methodology, scientometric analysis, and qualitative discussion, 113 journal articles were retrieved from the Scopus database, analyzed with VOSviewer, and further examined regarding mainstream topics, research gaps, and future research directions. The results revealed significant findings from the co-occurrence analysis of keywords, countries, and documents. Additionally, this study identified four primary research topics: (1) TENG, PENG, and other power sources; (2) wearable, flexible, stretchable, and tactile electronics for sensing; (3) industry 4.0; (4) HMI devices and systems. Based on the qualitative discussion of these topics, corresponding research gaps and future research directions were also identified. Eventually, this review would assist scholars and practitioners in the construction sector to better understand the existing body of knowledge and lay the foundation for future research.