{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T16:33:25Z","timestamp":1791909205149,"version":"4.3.4"},"reference-count":27,"publisher":"SAGE Publications","issue":"6","license":[{"start":{"date-parts":[[2024,5,17]],"date-time":"2024-05-17T00:00:00Z","timestamp":1715904000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"Welsh Government\u2019s SMART Cymru programme","award":["2019\/ED\/054"],"award-info":[{"award-number":["2019\/ED\/054"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["J Diabetes Sci Technol"],"published-print":{"date-parts":[[2025,11]]},"abstract":"<jats:sec>\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>Self-monitoring of glucose is important to the successful management of diabetes; however, existing monitoring methods require a degree of invasive measurement which can be unpleasant for users. This study investigates the accuracy of a noninvasive glucose monitoring system that analyses spectral variations in microwave signals.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>An open-label, pilot design study was conducted with four cohorts (N = 5\/cohort). In each session, a dial-resonating sensor (DRS) attached to the wrist automatically collected data every 60 seconds, with a novel artificial intelligence (AI) model converting signal resonance output to a glucose prediction. Plasma glucose was measured in venous blood samples every 5 minutes for Cohorts 1 to 3 and every 10 minutes for Cohort 4. Accuracy was evaluated by calculating the mean absolute relative difference (MARD) between the DRS and plasma glucose values.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>Accurate plasma glucose predictions were obtained across all four cohorts using a random sampling procedure applied to the full four-cohort data set, with an average MARD of 10.3%. A statistical analysis demonstrates the quality of these predictions, with a surveillance error grid (SEG) plot indicating no data pairs falling into the high-risk zones.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions:<\/jats:title>\n                    <jats:p>These findings show that MARD values approaching accuracies comparable to current commercial alternatives can be obtained from a multiparticipant pilot study with the application of AI. Microwave biosensors and AI models show promise for improving the accuracy and convenience of glucose monitoring systems for people with diabetes.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/19322968241252819","type":"journal-article","created":{"date-parts":[[2024,5,17]],"date-time":"2024-05-17T08:38:00Z","timestamp":1715935080000},"page":"1546-1553","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":7,"title":["Using Artificial Intelligence to Improve the Accuracy of a Wrist-Worn, Noninvasive Glucose Monitor: A Pilot Study"],"prefix":"10.1177","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2971-6235","authenticated-orcid":false,"given":"Muhammad Rafaqat Ali","family":"Qureshi","sequence":"first","affiliation":[{"name":"Afon Technology, Monmouthshire, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephen Charles","family":"Bain","sequence":"additional","affiliation":[{"name":"Joint Clinical Research Facility, Institute of Life Science 2, Swansea University, Swansea, UK"},{"name":"Diabetes Research Group, Faculty of Medicine, Health and Life Science, Swansea University, Swansea, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephen","family":"Luzio","sequence":"additional","affiliation":[{"name":"Diabetes Research Group, Faculty of Medicine, Health and Life Science, Swansea University, Swansea, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8888-8945","authenticated-orcid":false,"given":"Consuelo","family":"Handy","sequence":"additional","affiliation":[{"name":"Afon Technology, Monmouthshire, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel J.","family":"Fowles","sequence":"additional","affiliation":[{"name":"Afon Technology, Monmouthshire, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7528-3867","authenticated-orcid":false,"given":"Bradley","family":"Love","sequence":"additional","affiliation":[{"name":"Afon Technology, Monmouthshire, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kathie","family":"Wareham","sequence":"additional","affiliation":[{"name":"Joint Clinical Research Facility, Institute of Life Science 2, Swansea University, Swansea, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lucy","family":"Barlow","sequence":"additional","affiliation":[{"name":"Joint Clinical Research Facility, Institute of Life Science 2, Swansea University, Swansea, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6022-862X","authenticated-orcid":false,"given":"Gareth J.","family":"Dunseath","sequence":"additional","affiliation":[{"name":"Diabetes Research Group, Faculty of Medicine, Health and Life Science, Swansea University, Swansea, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joel","family":"Crane","sequence":"additional","affiliation":[{"name":"Diabetes Research Group, Faculty of Medicine, Health and Life Science, Swansea University, Swansea, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Isamar Carrillo","family":"Masso","sequence":"additional","affiliation":[{"name":"Afon Technology, Monmouthshire, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julia A. M.","family":"Ryan","sequence":"additional","affiliation":[{"name":"Afon Technology, Monmouthshire, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2568-8396","authenticated-orcid":false,"given":"Mohamed Sabih","family":"Chaudhry","sequence":"additional","affiliation":[{"name":"Afon Technology, Monmouthshire, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2024,5,17]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1177\/193229681300700225"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1089\/dia.2005.7.612"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcf.2022.07.013"},{"key":"e_1_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2016.19975"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.1089\/dia.2018.0080"},{"key":"e_1_3_3_7_2","doi-asserted-by":"publisher","DOI":"10.1089\/dia.2019.0132"},{"key":"e_1_3_3_8_2","unstructured":"Hoskins M. \u201cNoninvasive\u201d glucose monitoring for diabetes: where is it now? [Online]. 2022. https:\/\/www.healthline.com\/diabetesmine\/non-invasive-diabetes-technology. Accessed January 26 2022."},{"issue":"1","key":"e_1_3_3_9_2","first-page":"12","article-title":"Novel microwave based non-invasive glucose device","volume":"1","author":"Qureshi MRA","year":"2020","unstructured":"Qureshi MRA, Shillingford J, Handy CM, et al. Novel microwave based non-invasive glucose device. 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