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In-depth correlation analysis between tear glucose and blood glucose using a wireless smart contact lens

Author

Listed:
  • Wonjung Park

    (Yonsei University
    Yonsei University)

  • Hunkyu Seo

    (Yonsei University
    Yonsei University)

  • Jeongho Kim

    (Kyungpook National University)

  • Yeon-Mi Hong

    (Yonsei University
    Yonsei University)

  • Hayoung Song

    (Yonsei University
    Yonsei University)

  • Byung Jun Joo

    (Yonsei University
    Yonsei University)

  • Sumin Kim

    (Yonsei University
    Yonsei University)

  • Enji Kim

    (Yonsei University
    Yonsei University)

  • Che-Gyem Yae

    (Kyungpook National University School of Medicine)

  • Jeonghyun Kim

    (Kwangwoon University)

  • Jonghwa Jin

    (Kyungpook National University Hospital)

  • Joohee Kim

    (Biomedical Research Division Korea Institute of Science and Technology)

  • Yong-ho Lee

    (Yonsei University College of Medicine
    Yonsei University College of Medicine
    Severance Hospital)

  • Jayoung Kim

    (Yonsei University College of Medicine)

  • Hong Kyun Kim

    (Kyungpook National University
    Kyungpook National University School of Medicine
    Kyungpook National University Hospital)

  • Jang-Ung Park

    (Yonsei University
    Yonsei University
    Yonsei University College of Medicine
    Yonsei University)

Abstract

Tears have emerged as a promising alternative to blood for diagnosing diabetes. Despite increasing attempts to measure tear glucose using smart contact lenses, the controversy surrounding the correlation between tear glucose and blood glucose still limits the clinical usage of tears. Herein, we present an in-depth investigation of the correlation between tear glucose and blood glucose using a wireless and soft smart contact lens for continuous monitoring of tear glucose. This smart contact lens is capable of quantitatively monitoring the tear glucose levels in basal tears excluding the effect of reflex tears which might weaken the relationship with blood glucose. Furthermore, this smart contact lens can provide an unprecedented level of continuous tear glucose data acquisition at sub-minute intervals. These advantages allow the precise estimation of lag time, enabling the establishment of the concept called ‘personalized lag time’. This demonstration considers individual differences and is successfully applied to both non-diabetic and diabetic humans, as well as in animal models, resulting in a high correlation.

Suggested Citation

  • Wonjung Park & Hunkyu Seo & Jeongho Kim & Yeon-Mi Hong & Hayoung Song & Byung Jun Joo & Sumin Kim & Enji Kim & Che-Gyem Yae & Jeonghyun Kim & Jonghwa Jin & Joohee Kim & Yong-ho Lee & Jayoung Kim & Hon, 2024. "In-depth correlation analysis between tear glucose and blood glucose using a wireless smart contact lens," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-47123-9
    DOI: 10.1038/s41467-024-47123-9
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    References listed on IDEAS

    as
    1. Wei Gao & Sam Emaminejad & Hnin Yin Yin Nyein & Samyuktha Challa & Kevin Chen & Austin Peck & Hossain M. Fahad & Hiroki Ota & Hiroshi Shiraki & Daisuke Kiriya & Der-Hsien Lien & George A. Brooks & Ron, 2016. "Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis," Nature, Nature, vol. 529(7587), pages 509-514, January.
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