Human body IoT systems based on the triboelectrification effect: energy harvesting, sensing, interfacing and communication

Abstract

In recent years, the internet of things (IoT) has been progressing rapidly with the integration of technologies in various fields. At this stage, triboelectric nanogenerator (TENG) technology based on the triboelectrification effect and electrostatic induction has revealed great potential in various fields, including energy harvesting and sensing. Due to the improvements of configurations and materials, TENGs offer flexibility, compatibility, and stability, enabling novel auxiliary applications by harvesting and converting human mechanical energy. In this review, we first propose a concept of the TENG-based human body IoT system, consisting of energy harvesting, sensing, and interfacing, to effectively obtain, monitor and manage human motion and physical status information. Then, we present a comprehensive overview of such an IoT system from the three aforementioned focuses. Firstly, studies on human body energy harvesting are categorized according to the configurations and materials of TENGs. Secondly, based on the high sensitivity of TENGs, wearable and implantable sensors are investigated to develop the potential of human motion or physiological signal monitoring. Thirdly, the representative studies on TENG-based interfacing between human body and external electronics by using a microcontroller (MCU) are investigated based on various interactive types. Furthermore, we statistically discuss the developmental trend of TENGs in the above focused fields, and the materials suitable for TENGs to offer inspirational angles for future research. We also elaborate the proposed TENG-based human body IoT system by introducing various integrated modules with multi-functions. Finally, we systematically present promising prospects for future research directions and challenges from the perspectives of materials, power management, and communication. This review is dedicated to offering critical insights into the development of TENG-based human body IoT systems.