AI-driven wearable smart textiles: a review of research trends and frontiers

Abstract

The integration of Artificial Intelligence (AI) with wearable smart textiles is transforming passive fabrics into active systems capable of sensing, responding, and adapting to environmental and user-specific stimuli. Despite growing interest, a comprehensive quantitative analysis of this interdisciplinary field remains lacking. This study conducts a bibliometric and visual analysis of publications from 2000 to 2025 from the Web of Science (WoS) Core Collection, utilizing Visualization of Similarities viewer (VOSviewer), CiteSpace, and Bibliometrix to examine publication trends, collaboration networks, thematic evolution, and intellectual structures. Results indicate rapid growth in publications, with China, the United States, and South Korea leading a highly collaborative international network. The field exhibits strong interdisciplinary connections among materials science, nanotechnology, electronic engineering, and AI-based data analytics. Key research themes include fiber-based nanogenerators, while emerging trends focus on AI-sensor integration, sustainable materials, and multifunctional applications. This study constructs a knowledge framework and identifies future directions such as AI algorithm miniaturization, self-powered sensing, eco-friendly material industrialization, and deeper scenario-based applications. These findings address the gap in macro-level analysis and offer strategic guidance to advance research and innovation in AI-enhanced wearable smart textiles.