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Wearable Sensor Patch with Hydrogel Microneedles for In Situ Analysis of Interstitial Fluid.

Yumin DaiJames K NolanEmilee MadsenMarco FratusJunsang LeeJinyuan ZhangJongcheon LimSeokkyoon HongMuhammad Ashraful AlamJacqueline C LinnesHyowon Hugh LeeChi-Hwan Lee
Published in: ACS applied materials & interfaces (2023)
Continuous real-time monitoring of biomarkers in interstitial fluid is essential for tracking metabolic changes and facilitating the early detection and management of chronic diseases such as diabetes. However, developing minimally invasive sensors for the in situ analysis of interstitial fluid and addressing signal delays remain a challenge. Here, we introduce a wearable sensor patch incorporating hydrogel microneedles for rapid, minimally invasive collection of interstitial fluid from the skin while simultaneously measuring biomarker levels in situ. The sensor patch is stretchable to accommodate the swelling of the hydrogel microneedles upon extracting interstitial fluid and adapts to skin deformation during measurements, ensuring consistent sensing performance in detecting model biomarker concentrations, such as glucose and lactate, in a mouse model. The sensor patch exhibits in vitro sensitivities of 0.024 ± 0.002 μA mM -1 for glucose and 0.0030 ± 0.0004 μA mM -1 for lactate, with corresponding linear ranges of 0.1-3 and 0.1-12 mM, respectively. For in vivo glucose sensing, the sensor patch demonstrates a sensitivity of 0.020 ± 0.001 μA mM -1 and a detection range of 1-8 mM. By integrating a predictive model, the sensor patch can analyze and compensate for signal delays, improving calibration reliability and providing guidance for potential optimization in sensing performance. The sensor patch is expected to serve as a minimally invasive platform for the in situ analysis of multiple biomarkers in interstitial fluid, offering a promising solution for continuous health monitoring and disease management.
Keyphrases
  • minimally invasive
  • drug delivery
  • mouse model
  • wound healing
  • type diabetes
  • mental health
  • blood glucose
  • robot assisted
  • high throughput
  • blood pressure
  • adipose tissue
  • skeletal muscle
  • climate change