A wireless sweat sensing with a pH- based correlation model for continuous glucose monitoring and diabetes management during exercise

• 成果类型: Article
• 署名作者: Zhang, Yingying; Zhang, Senhao; Yang, Ying; Tao, Lin; Yu, Fengfei; Song, Chaoyun; Guo, Kai; Zhu, Jia; Lin, Yuan; Yang, Furong; Yang, Hongbo; Cheng, Huanyu
• 署名单位: Chinese Academy of Sciences; University of Science & Technology of China, CAS; Chinese Academy of Sciences; Suzhou Institute of Biomedical Engineering & Technology, CAS; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; University of London; King's College London; University of Electronic Science & Technology of China
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-8424; 1091-6490
• DOI: 10.1073/pnas.2532127123
• 发表日期: 2026-03-09
• 页码: 2532127123
• 关键词: pH-based sweat-blood glucose correlation model; flexible sweat-sensing platform; glucose and pH monitoring; noninvasive CGM; glucose management during exercise; performance; ELECTRODE; sensors

摘要

In situ monitoring of sweat glucose during exercise can provide a real- time and continuous assessment of blood glucose dynamics. However, the relatively poor correlation between sweat and blood glucose concentrations during exercise makes it challenging for blood glucose management (BGM) during exercise therapy for diabetes, along with training for athletes and fitness enthusiasts. This work presents a flexible wireless sweat glucose and pH sensing platform integrated with a pH- based correlation model to accurately predict the continuous changes in blood glucose. The pH- based correlation model calibrates enzyme activity changes in glucose oxidase and accounts for the effects of sweat dilution and filtering during paracellular transport of glucose from interstitial fluid and plasma to sweat during exercise. The correlation model has been validated in both healthy individuals and diabetic patients, revealing distinct blood glucose dynamic patterns between the two cohorts. The observed different glucose fluctuations after the intake of various nutritive foods further facilitate the management of diabetes and allow for the identification of hypo- /hyperglycemic risks during training or fitness exercise. diabetes management through effective treatment evaluation and can also provide early prevention for the at- risk population and reduce or even reverse diabetes.