Journal article 699 views 95 downloads
Using Artificial Intelligence to Improve the Accuracy of a Wrist-Worn, Noninvasive Glucose Monitor: A Pilot Study
Muhammad Rafaqat Ali Qureshi 
,
Steve Bain ,
Steve Luzio ,
Consuelo Handy ,
Daniel J. Fowles,
Bradley Love ,
Kathleen Wareham,
Lucy Barlow,
Gareth Dunseath ,
Joel Crane,
Isamar Carrillo Masso,
Julia A. M. Ryan,
Mohamed Sabih Chaudhry
,
Steve Bain ,
Steve Luzio ,
Consuelo Handy ,
Daniel J. Fowles,
Bradley Love ,
Kathleen Wareham,
Lucy Barlow,
Gareth Dunseath ,
Joel Crane,
Isamar Carrillo Masso,
Julia A. M. Ryan,
Mohamed Sabih Chaudhry
Journal of Diabetes Science and Technology
Swansea University Authors:
Steve Bain , Steve Luzio , Kathleen Wareham, Lucy Barlow, Gareth Dunseath , Joel Crane
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PDF | Accepted Manuscript
Author accepted manuscript document released under the terms of a Creative Commons CC-BY licence using the Swansea University Research Publications Policy (rights retention).
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DOI (Published version): 10.1177/19322968241252819
Abstract
Using Artificial Intelligence to Improve the Accuracy of a Wrist-Worn, Noninvasive Glucose Monitor: A Pilot Study
| Published in: | Journal of Diabetes Science and Technology |
|---|---|
| ISSN: | 1932-2968 1932-2968 |
| Published: |
SAGE Publications
2024
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| Online Access: |
Check full text
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa67315 |
| Keywords: |
Blood glucose self-monitoring, diabetes mellitus, microwaves, noninvasive glucose monitoring, radio frequency, wearable electronic devices |
|---|---|
| College: |
Faculty of Medicine, Health and Life Sciences |
| Funders: |
This work was supported by the Welsh Government’s SMARTCymru program, backed by the EU’s European Regional Development Fund (grant no. 2019/ED/054). |