Wearable smart sensors for monitoring human motion have emerged as an active area of research due to their potential applications in healthcare, sports performance, and human–machine interaction. These devices must not only provide accurate sensing capabilities but also be flexible, portable, and comfortable to integrate seamlessly into daily life. Conventional textiles, while widely used, are no longer sufficient to meet the functional demands of contemporary users. As a result, the textile industry is evolving toward functionalization and intelligence, with smart fabrics gaining increasing attention.

A key enabler of smart textiles is their ability to integrate sensing functions directly into fabrics. Current wearable devices, such as smartwatches and fitness bands, can monitor physiological parameters, including heart rate, respiration, and pulse. However, embedding comparable sensing functionalities directly into textiles remains a considerable challenge, particularly with respect to long-term washability, signal drift during repeated deformation, and the preservation of stable electromechanical performance under realistic wearing conditions.

Smart fabrics must be flexible, foldable, skin-compatible, lightweight, breathable, and durable, while maintaining rapid signal transmission and reliable sensing performance. These requirements are typically met by incorporating flexible sensors that transduce external mechanical or thermal stimuli into electrical signals.

Significant progress has been made in developing fabric-based sensors with enhanced electromechanical properties. These studies highlight diverse strategies for imparting sensing functions to fabrics, although achieving an optimal balance among comfort, durability, and high-performance sensing remains a challenge. Several fabrication strategies have been employed to realize conductive fabrics for sensing applications, but challenges persist in achieving high sensitivity, reproducibility, and washability under realistic usage conditions.

To address them, Ke et al. present a knitted sensor wristband, designed for wrist posture recognition, which is reported by Frontiers of Materials Science. Unlike traditional knitted strain sensors that primarily rely on material modification or multilayer architectures to enhance sensitivity, this study emphasizes the synergistic role of selecting conductive yarns and knit architecture. In particular, the combination of a copper-coated yarn with a 1 × 1 rib stitch structure enables a favorable balance between moderate baseline resistance, high strain sensitivity, and mechanical robustness. By systematically varying conductive yarn types, knitting structures (1 × 1 rib, rib half-air layer, and rib air layer stitch), and stitch densities, they investigate the combined effects on the electromechanical properties of conductive fabrics. Resistance behaviors were analyzed to identify the optimal combination of yarn material, fabric architecture, and density. The best-performing configuration was integrated into a wristband and evaluated using wrist-bending experiments to assess sensitivity, repeatability, and posture recognition.

This study not only provides fundamental insights into the role of textile architecture in sensor performance but also offers practical guidelines for designing comfortable, durable, and high-performance wearable sensors compatible with scalable textile manufacturing and long-term wearable use.
DOI：10.1007/s11706-026-0758-z