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Evaluation of a Continuous Blood Glucose Monitor: A Novel and Non-Invasive Wearable Using Bioimpedance Technology.
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- Author(s): Sanai F;Sanai F; Sahid AS; Sahid AS; Huvanandana J; Huvanandana J; Spoa S; Spoa S; Boyle LH; Boyle LH; Hribar J; Hribar J; Wang DT; Wang DT; Kwan B; Kwan B; Colagiuri S; Colagiuri S; Colagiuri S; Cox SJ; Cox SJ; Telfer TJ; Telfer TJ
- Source:
Journal of diabetes science and technology [J Diabetes Sci Technol] 2023 Mar; Vol. 17 (2), pp. 336-344. Date of Electronic Publication: 2021 Oct 29.- Publication Type:
Journal Article; Observational Study; Research Support, Non-U.S. Gov't- Language:
English - Source:
- Additional Information
- Source: Publisher: Sage Country of Publication: United States NLM ID: 101306166 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1932-2968 (Electronic) Linking ISSN: 19322968 NLM ISO Abbreviation: J Diabetes Sci Technol Subsets: MEDLINE
- Publication Information: Publication: 2014- : Thousand Oaks, CA : Sage
Original Publication: Foster City, CA : Diabetes Technology Society - Subject Terms:
- Abstract: Background: Frequent blood glucose level (BGL) monitoring is essential for effective diabetes management. Poor compliance is common due to the painful finger pricking or subcutaneous lancet implantation required from existing technologies. There are currently no commercially available non-invasive devices that can effectively measure BGL. In this real-world study, a prototype non-invasive continuous glucose monitoring system (NI-CGM) developed as a wearable ring was used to collect bioimpedance data. The aim was to develop a mathematical model that could use these bioimpedance data to estimate BGL in real time.
Methods: The prototype NI-CGM was worn by 14 adult participants with type 2 diabetes for 14 days in an observational clinical study. Bioimpedance data were collected alongside paired BGL measurements taken with a Food and Drug Administration (FDA)-approved self-monitoring blood glucose (SMBG) meter and an FDA-approved CGM. The SMBG meter data were used to improve CGM accuracy, and CGM data to develop the mathematical model.
Results: A gradient boosted model was developed using a randomized 80-20 training-test split of data. The estimated BGL from the model had a Mean Absolute Relative Difference (MARD) of 17.9%, with the Parkes error grid (PEG) analysis showing 99% of values in clinically acceptable zones A and B.
Conclusions: This study demonstrated the reliability of the prototype NI-CGM at collecting bioimpedance data in a real-world scenario. These data were used to train a model that could successfully estimate BGL with a promising MARD and clinically relevant PEG result. These results will enable continued development of the prototype NI-CGM as a wearable ring. - References: Clin Diabetes. 2020 Jan;38(1):10-38. (PMID: 31975748)
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Diabetes Obes Metab. 2017 Jul;19(7):1051-1055. (PMID: 28205324) - Contributed Indexing: Keywords: blood glucose; continuous glucose monitoring system; device; diabetes; model; non-invasive
- Accession Number: 0 (Blood Glucose)
- Publication Date: Date Created: 20211029 Date Completed: 20230312 Latest Revision: 20230331
- Publication Date: 20240628
- Accession Number: PMC10012362
- Accession Number: 10.1177/19322968211054110
- Accession Number: 34711074
- Source:
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