Deep learning-assisted 10-μL single droplet-based viscometry for human aqueous humor.

Journal: Biosensors & bioelectronics
Published Date: May 2, 2025

Abstract

Probing the viscosity of human aqueous humor is crucial for optimizing micro-tube shunts in glaucoma treatment. However, conventional viscometers are not suitable for aqueous humor due to the limited sample volume-only tens of microliters-that can be safely extracted without causing permanent ocular damage. Here, we present an artificial intelligence-assisted microfluidic viscometry for measuring 10-μL aqueous humor collected at the point of care. Our approach involves injecting a single droplet of the sample into a microfluidic chip using hydrostatic pressure, minimizing interfacial effects with surfactants and hydrophobic coatings, and analyzing the sample flow using a deep learning-based detection scheme. For the first time, we have measured the viscosity of a 10-μL human aqueous humor and observed approximately 30 % variation between individuals. These individual differences in aqueous humor viscosity should be considered when designing microtube shunts for glaucoma treatment. Our method paves the way for the viscometry of small-volume biofluids, enabling new diagnostic and therapeutic applications in biomedical technology.

Authors

  • Hyunsung Park
    Department of Physics, Chungbuk National University, Cheongju, 2864, South Korea.
  • Junhong Park
    Department of Mechanical Engineering, Hanyang University, 222 Wangsimri-ro, Seongdong-gu, Seoul 04763, Korea.
  • Dongwon Kim
  • Dongeun Kim
    Department of Medical Device Management and Research, SAIHST, Sungkyunkwan University, Seoul, 06355, South Korea.
  • Wonho Jhe
    Department of Physics & Astronomy, Center for 0D Nanofluidics, Seoul National University, Seoul, 08826, South Korea; John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, United States. Electronic address: whjhe@snu.ac.kr.
  • Jong Chul Han
    Department of Medical Device Management and Research, SAIHST, Sungkyunkwan University, Seoul, 06355, South Korea; Department of Ophthalmology, Samsung Medical Center, Sungkyunkwan University, Seoul, 06351, South Korea. Electronic address: heartmedic@skku.edu.
  • Manhee Lee
    Department of Physics, Chungbuk National University, Cheongju, 2864, South Korea. Electronic address: mlee@cbnu.ac.kr.

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