电致变色
可穿戴计算机
汗水
解耦(概率)
材料科学
生物传感器
计算机科学
可穿戴技术
纳米技术
墨水池
生物医学工程
人类健康
可视化
机制(生物学)
能量(信号处理)
人工智能
织物
光电子学
智能手表
功率(物理)
作者
Hang Tian,Yuhao Zhang,Shuhan Wang,Yingying Hao,Kun Wang,Wei Gu,Shihui Chen,Kerui Li,Qinghong Zhang,Xinxin Xiao,Yaogang Li,Hongzhi Wang,Chengyi Hou
摘要
ABSTRACT Noninvasive wearable sweat sensors are promising for personalized health management, yet their widespread adoption is hindered by complex multi‐component architectures, reliance on rigid batteries, and a lack of intuitive visual feedback. Herein, we propose a sweat‐powered metabolism‐to‐visual transduction mechanism that utilizes sweat as both an energy source and a detection target. A fabric‐based sweat electricity harvester is fabricated, which harnesses sweat energy to yield a stable power output, enabling battery‐free sensing operation. Coupled enzymatic sensing electrode–electrochromic display system translates sweat glucose concentration into directly perceptible color change. To overcome the subjective errors inherent in traditional colorimetry, a neural network‐based smartphone application is employed to provide precise quantitative visual readouts, achieving highly accurate estimation of sweat glucose (R 2 = 0.997) comparable to commercial assay kits in on‐body evaluation on human subjects. By successfully decoupling wearable sensors from rigid power sources while fusing self‐powered electrochromic displays with AI‐assisted digital readouts, this lightweight textile platform establishes an on‐demand strategy for user‐friendly, and intelligent metabolic monitoring.
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