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A Reproducible Bioimpedance Transducer for Insulin Noninvasive Measurement - CERN Document Server

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Article
Title A Reproducible Bioimpedance Transducer for Insulin Noninvasive Measurement
Author(s) Arpaia, Pasquale (CERN ; Naples U.) ; Mancino, Francesca (Naples U.) ; Moccaldi, Nicola (Naples U.)
Publication 2023
Number of pages 11
In: IEEE Trans. Instrum. Meas. 72 (2023) 1-11
DOI 10.1109/tim.2023.3264037
Subject category Health Physics and Radiation Effects
Abstract A bioimpedance transducer is proposed for noninvasive monitoring of insulin bioavailability after subcutaneous injection. The insulin bioavailability is assessed indirectly by measuring the local impedance variation due to the drug disappearance from the injection volume. The instrument allows to manage the extreme variability in insulin response by patients with diabetes due to skin conditions and/or alterations such as lipodystrophy. In this way, the transducer can also be considered as a key component for new generation of artificial pancreas. The instrument achieves the state-of-the-art accuracy and uncertainty. Intraindividual reproducibility also improved with respect to previous studies. Moreover, the feasibility of an absorption measurement is proven. After presenting the concept design and the prototype, the metrological characterization during: 1) laboratory (on passive electrical components); 2) in vitro (on eggplants); and 3) in vivo (on a human subject) experiments is reported. In laboratory tests, typical percentage deterministic errors of 1% on magnitude and phase were obtained. The mean 1-σしぐま repeatability of 0.05% was obtained for both impedance magnitude and phase. The in vitro tests were aimed to improve the reproducibility by comparing the electrical behavior of insulin and vehicle in eggplants. During in vivo tests, a decrease in percentage 1-σしぐま intraindividual reproducibility was reported with respect to the state-of-the-art (from more than 200% to 36%), as the impedance magnitude is concerned. In a clinical application framework, an accuracy of 9 µl was obtained by means of a second-order polynomial model. The uncertainty was 4.2 µl, well below the typical volume of one insulin unit (10.0 µl).
Copyright/License publication: (License: CC-BY-4.0)

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