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Sweat and air permeable electronics enabled by engineered hierarchical fabric system for exercise management

  • Qiuqian Ou (Co-first Author)
  • , Hongwei Chu (Co-first Author)
  • , Yujian Liu
  • , Liangling Cai
  • , Zhenhe Huang
  • , Dan Li
  • , Jiating Lin
  • , Yue Hu
  • , Jiyu Li
  • , Peng Li
  • , Jiao Yang*
  • , Xinge Yu*
  • , Yingchun Li*
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

Scientific exercise monitoring is significant for injury risk prevention and training outcome promotion. Wearable biosensing technologies have emerged as transformative tools for real-time, in-situ physiological state profiling through dynamic biomarker detection during exercise activities. However, current studies remain suboptimal for practical exercise management due to inherent constraints including single-analyte detection paradigms, limited permeability and breathability, and inadequate thermoregulatory performance. Here, we present a novel wearable composite fabric system engineered for multiplex sweat biomarker monitoring while delivering unprecedented wear comfort. The hierarchical architecture was achieved through strategic integration of interwoven fiber-based sensor arrays with conventional textiles, augmented by bilateral deposition of microbead-enhanced polyvinylidene difluoride (PVDF) and polyacrylonitrile (PAN) electrospun nanofiber membranes. The porous matrix, Janus hierarchical gradient, and microbead-mediated interfacial engineering render this fabric system with excellent breathability of 13 mm/s, water vapor transmission rate of 468.9 g/m2/h, and solar reflectance of 96.2%. Systematic validation revealed the system’s capabilities in multiplex biomarker tracking during diverse exercise scenarios, machine learning-powered fatigue assessment, and scientific exercise regimen evaluation. This work establishes a universal framework for developing wearable platforms with reliable sensing functionality and wear comfort, facilitating effective personalized exercise healthcare management. © The Author(s) 2026.
Original languageEnglish
Article number241
Number of pages16
JournalMicrosystems and Nanoengineering
Volume12
Online published22 Jun 2026
DOIs
Publication statusPublished - 2026

Funding

This work was financially supported by This work was financially supported by Shenzhen Medical Research Fund (D2402018), Shenzhen Science and Technology Program (KCXFZ20230731094701003), the National Natural Science Foundation of China (82373831), Key Program of Natural Science Foundation of Shenzhen (JCYJ20220818102218039), and the Plan of Science and Technology in Shenzhen (SYSPG20241211173609007).

Publisher's Copyright Statement

  • This full text is made available under CC-BY-NC-ND 4.0. https://creativecommons.org/licenses/by-nc-nd/4.0/

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