{
  "abstract": "Accurate continuous glucose monitoring (CGM) is essential for diabetes management, yet non-invasive CGM remains challenging. Universal \"one-sensor-fits-all\" approaches often fail, because correlations between non-invasive physiological readouts and blood glucose (BG) are highly individualized. Here, we propose a personalized \"Adaptive Non-invasive CGM\" methodology, which integrates a short-term minimally invasive CGM (MI-CGM) module for measuring interstitial fluid glucose, and a long-term non-invasive CGM (NI-CGM) module based on metabolic heat conformation. During a ~2-days training, the NI-CGM learns accurate sensing from the MI-CGM via GRU-based AI model, forming patient-specific sensor. The MI-CGM is then removed, leaving only the NI-CGM for long-term monitoring. In a 5-day CGM test, the system achieved MARD ~15.6%. This method also demonstrated good reproducibility and maintained reasonable accuracy (MARD ~23.9%) during long-term interval use (>2 months). This personalized approach offers a pathway from conventional \"one-sensor-fits-all\" strategies toward individualized sensor development, potentially mitigating inter-patient variability and non-invasive monitoring inaccuracies.",
  "abstract_shown": true,
  "affiliations": [
    "State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China.",
    "Guangdong Provincial Key Laboratory of Sensor Technology and Biomedical Instrument, School of Biomedical Engineering, Sun Yat-sen University, Shenzhen, China.",
    "Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China.",
    "Shenzhen SiSensing Co., Ltd, Shenzhen, China.",
    "National Innovation Center for Advanced Medical Devices, Shenzhen, China.",
    "Department of Endocrinology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.",
    "The First Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Guangzhou, China.",
    "National Key Lab of Autonomous Intelligent Unmanned Systems, Beijing Institute of Technology, Beijing, China.",
    "School of Intelligent Systems Engineering, Sun Yat-Sen University, Shenzhen, China.",
    "Laboratory of Biomaterials and Translational Medicine, Center for Nanomedicine, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.",
    "State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China. huangxsh35@mail.sysu.edu.cn.",
    "State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China. xiexi27@mail.sysu.edu.cn.",
    "Guangdong Provincial Key Laboratory of Sensor Technology and Biomedical Instrument, School of Biomedical Engineering, Sun Yat-sen University, Shenzhen, China. xiexi27@mail.sysu.edu.cn.",
    "The First Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Guangzhou, China. xiexi27@mail.sysu.edu.cn."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 20,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Chuanjie Yao"
    },
    {
      "affs": [
        0
      ],
      "name": "Lukang Gao"
    },
    {
      "affs": [
        0
      ],
      "name": "Xinze Wang"
    },
    {
      "affs": [
        0
      ],
      "name": "Haolin Wang"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Shuang Huang"
    },
    {
      "affs": [
        2
      ],
      "name": "Guanbin Li"
    },
    {
      "affs": [
        3
      ],
      "name": "Xiongqi Han"
    },
    {
      "affs": [
        0
      ],
      "name": "Hanqi Yang"
    },
    {
      "affs": [
        0
      ],
      "name": "Zhengjie Liu"
    },
    {
      "affs": [
        4
      ],
      "name": "Shanshan Liang"
    },
    {
      "affs": [
        5
      ],
      "name": "Peng Yun"
    },
    {
      "affs": [
        6
      ],
      "name": "Yunuo Wang"
    },
    {
      "affs": [
        7
      ],
      "name": "Yeyun Cai"
    },
    {
      "affs": [
        3
      ],
      "name": "Peikai Zhang"
    },
    {
      "affs": [
        8
      ],
      "name": "Yuanqing Wu"
    },
    {
      "affs": [
        9
      ],
      "name": "Mingqiang Li",
      "orcid": "0000-0002-5178-4138"
    },
    {
      "affs": [
        6
      ],
      "name": "Ji Wang",
      "orcid": "0000-0002-8631-3264"
    },
    {
      "affs": [
        0
      ],
      "name": "Hui-Jiuan Chen"
    },
    {
      "affs": [
        10
      ],
      "name": "Xinshuo Huang"
    },
    {
      "affs": [
        11,
        12,
        13
      ],
      "name": "Xi Xie",
      "orcid": "0000-0001-7406-8444"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/93djj8r3tczbh.bib",
  "cited_by": 0,
  "doi": "10.1038/s41467-026-74531-w",
  "fulltext_url": "https://europepmc.org/articles/PMC13720166",
  "id": "93djj8r3tczbh",
  "issns": [
    "2041-1723"
  ],
  "landing_url": "https://europepmc.org/article/MED/42957678",
  "language": "eng",
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Article"
    ],
    [
      "openalex",
      "2712|Diabetes Management and Research"
    ]
  ],
  "openalex": "W4413940413",
  "pdf_url": "https://europepmc.org/articles/PMC13720166?pdf=render",
  "pmcid": "PMC13720166",
  "pmid": "42957678",
  "published": "2026-09-28",
  "publisher": "Nature Publishing Group",
  "ris": "https://research.draconitic.com/paper/93djj8r3tczbh.ris",
  "sources": [
    {
      "first_seen": "2026-11-01T00:20:44Z",
      "native_id": "MED:42957678",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42957678"
    },
    {
      "first_seen": "2026-11-02T12:24:00Z",
      "native_id": "PMC13720166",
      "source": "pmc",
      "url": "https://doi.org/10.1038/s41467-026-74531-w"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2712|Diabetes Management and Research",
      "subfield": "endocrinology-metabolism"
    }
  ],
  "title": "Adaptive personalization for wearable non-invasive continuous glucose sensors.",
  "title_text": "Adaptive personalization for wearable non-invasive continuous glucose sensors.",
  "type": "peer-reviewed",
  "updated_at": "2026-11-03T12:21:06Z",
  "url": "https://research.draconitic.com/paper/93djj8r3tczbh",
  "venue": "Nature communications",
  "versions": []
}