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Smartphone-based colorimetric detection systems for glucose monitoring in the diagnosis and management of diabetes.
Kap, Özlem; Kiliç, Volkan; Hardy, John G; Horzum, Nesrin.
Afiliação
  • Kap Ö; Department of Engineering Sciences, Izmir Katip Çelebi University, 35620 Turkey. nesrin.horzum.polat@ikcu.edu.tr.
  • Kiliç V; Department of Electrical and Electronics Engineering, Izmir Katip Çelebi University, 35620 Turkey.
  • Hardy JG; Department of Chemistry, Lancaster University, Lancaster, Lancashire LA1 4YB, UK and Materials Science Institute, Lancaster University, Lancaster, Lancashire LA1 4YB, UK.
  • Horzum N; Department of Engineering Sciences, Izmir Katip Çelebi University, 35620 Turkey. nesrin.horzum.polat@ikcu.edu.tr.
Analyst ; 146(9): 2784-2806, 2021 May 04.
Article em En | MEDLINE | ID: mdl-33949379
Diabetes is a group of metabolic conditions resulting in high blood sugar levels over prolonged periods that affects hundreds of millions of patients worldwide. Measuring glucose concentration enables patient-specific insulin therapy, and is essential to reduce the severity of the disease, potential complications, and related mortalities. Recent advances and developments in smartphone-based colorimetric glucose detection systems are discussed in this review. The importance of glucose monitoring, data collection, transfer, and analysis, via non-invasive/invasive methods is highlighted. The review also presents various approaches using 3D-printed materials, screen-printed electrodes, polymer templates, designs allowing multiple glucose analysis, bioanalytes and/or nanostructures for glucose detection. The positive effects of advances in improving the performance of smartphone-based platforms are introduced along with future directions and trends in the application of emerging technologies in smartphone-based diagnostics.
Assuntos

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Colorimetria / Diabetes Mellitus Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Revista: Analyst Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Colorimetria / Diabetes Mellitus Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Revista: Analyst Ano de publicação: 2021 Tipo de documento: Article