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<p>Reverse iontophoresis (RI) is a promising non-invasive, wearable technology for the transdermal extraction of interstitial fluid (ISF), which contains rich biomarkers relevant to health status. Despite the advancement of wearable sensors, this technology is still restricted for accurate non-invasive biomarkers detection. The main challenge lies in the instability of ISF extraction during RI. We found that this instability is primarily caused by the skin surface pH variations because of the interaction between the RI-induced H<sup>+</sup> movement and the skin recovery ability. Here, we investigated how the skin surface pH affected RI, theoretically and experimentally; and developed a wearable device and a calibration method to enable accurate non-invasive ISF glucose detection, accordingly. The result showed that glucose prediction accuracy was markedly improved, with mean absolute relative difference (MARD) decreased from 34.44% to 14.78% across both healthy and diabetic volunteers.</p>

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pH calibration allows accurate glucose detection in interstitial fluid via reverse iontophoresis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月24日

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  • Wangwang Zhu,
  • Haixia Yu,
  • Wenjun Li,
  • Xi Li,
  • Hao Zheng,
  • Chengcheng Li,
  • Xingguo Zhang,
  • Chenxi Jin,
  • Mutian Wang,
  • Jiaqi Hou,
  • Youhao Liu,
  • Yuxiao Ma,
  • Zhongxu Zhou,
  • Miao Deng,
  • Peng Guo,
  • Mingzhen Li,
  • Zhenqiang Song,
  • Zhihua Pu,
  • Dachao Li

摘要

Reverse iontophoresis (RI) is a promising non-invasive, wearable technology for the transdermal extraction of interstitial fluid (ISF), which contains rich biomarkers relevant to health status. Despite the advancement of wearable sensors, this technology is still restricted for accurate non-invasive biomarkers detection. The main challenge lies in the instability of ISF extraction during RI. We found that this instability is primarily caused by the skin surface pH variations because of the interaction between the RI-induced H+ movement and the skin recovery ability. Here, we investigated how the skin surface pH affected RI, theoretically and experimentally; and developed a wearable device and a calibration method to enable accurate non-invasive ISF glucose detection, accordingly. The result showed that glucose prediction accuracy was markedly improved, with mean absolute relative difference (MARD) decreased from 34.44% to 14.78% across both healthy and diabetic volunteers.