Over the years, triboelectric nanogenerators (TENGs) have emerged as a promising technology for self-powered health monitoring systems. They enabled real-time, non-invasive and sustainable collection of physiological data, making them appealing for monitoring human health. TENGs are compact in size and have potential to effectively track vital signs. Such nanogenerators have become more efficient and smaller, so to be considered for a multitude of different human health monitoring applications. As TENGs gain momentum in human health monitoring, careful foresight is essential to ensure their reliable performance in complex biological environments. Key considerations include selecting biocompatible materials that do not harm recipients, optimizing the mechanical and biological properties of the devices, and understanding their potential lifespan within the dynamic conditions of the human body. While significant progress has been made in addressing these parameters, increasing attention is also being given to integrating artificial intelligence (AI) for rapid and efficient analysis of biosensor data generated by TENGs. This review highlights these developments and outlines future directions for advancing TENGs in health monitoring applications.
Moheth et al. (Sun,) studied this question.
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