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DC Field | Value | Language |
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dc.contributor.author | Cano-Garcia, H | - |
dc.contributor.author | Kshirsagar, R | - |
dc.contributor.author | Pricci, R | - |
dc.contributor.author | Teyeb, A | - |
dc.contributor.author | O’brien, F | - |
dc.contributor.author | Saha, S | - |
dc.contributor.author | Kosmas, P | - |
dc.contributor.author | Kallos, E | - |
dc.date.accessioned | 2022-02-10T18:05:20Z | - |
dc.date.available | 2022-02-10T18:05:20Z | - |
dc.date.issued | 2021-05-10 | - |
dc.identifier | ORCiD: Helena Cano-Garcia https://orcid.org/0000-0002-7128-3859 | - |
dc.identifier | ORCiD: Rohit Kshirsagar https://orcid.org/0000-0001-7796-6928 | - |
dc.identifier | ORCiD: Ahmed Teyeb https://orcid.org/0000-0003-0300-1845 | - |
dc.identifier | ORCiD: Panagiotis Kosmas https://orcid.org/0000-0001-9759-2820 | - |
dc.identifier | 3275 | - |
dc.identifier.citation | Cano-Garcia, H.et al. (2021) 'Enhancing the Accuracy of Non-Invasive Glucose Sensing in Aqueous Solutions Using Combined Millimeter Wave and Near Infrared Transmission', Sensors, 21, 3275, pp. 1 - 11. doi: 10.3390/s21093275. | en_US |
dc.identifier.issn | 1424-8220 | - |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/24101 | - |
dc.description | Data Availability Statement: Not applicable. | - |
dc.description | Patents: Patent applications GB21028808 and GB21028915 relate to work presented in this paper. | - |
dc.description.abstract | We reported measurement results relating to non-invasive glucose sensing using a novel multiwavelength approach that combines radio frequency and near infrared signals in transmission through aqueous glucose-loaded solutions. Data were collected simultaneously in the 37–39 GHz and 900–1800 nm electromagnetic bands. We successfully detected changes in the glucose solutions with varying glucose concentrations between 80 and 5000 mg/dl. The measurements showed for the first time that, compared to single modality systems, greater accuracy on glucose level prediction can be achieved when combining transmission data from these distinct electromagnetic bands, boosted by machine learning algorithms. | en_US |
dc.description.sponsorship | This research was funded partially by Innovate UK project 104554 (2019–2021). | en_US |
dc.format.extent | 1 - 11 | - |
dc.format.medium | Electronic | - |
dc.language.iso | en | en_US |
dc.publisher | MDPI | en_US |
dc.rights | Copyright © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). | - |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | - |
dc.subject | non-invasive; glucose; diabetes; monitor; near infrared; radiofrequency | en_US |
dc.title | Enhancing the accuracy of non-invasive glucose sensing in aqueous solutions using combined millimeter wave and near infrared transmission | en_US |
dc.type | Article | en_US |
dc.identifier.doi | https://doi.org/10.3390/s21093275 | - |
dc.relation.isPartOf | Sensors | - |
pubs.issue | 9 | - |
pubs.publication-status | Published | - |
pubs.volume | 21 | - |
dc.rights.license | https://creativecommons.org/licenses/by/4.0/legalcode.en | - |
dc.rights.holder | The authors | - |
Appears in Collections: | Brunel Innovation Centre |
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FullText.pdf | Copyright © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). | 1.48 MB | Adobe PDF | View/Open |
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