Selection of Noninvasive Features in Wrist-Based Wearable Sensors to Predict Blood Glucose Concentrations Using Machine Learning Algorithms

Glucose monitoring technologies allow users to monitor glycemic fluctuations (e.g., blood glucose levels). This is particularly important for individuals who have diabetes mellitus (DM). Traditional self-monitoring blood glucose (SMBG) devices require the user to prick their finger and extract a blo...

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Detalles Bibliográficos
Autores principales: Bogue-Jimenez, Brian, Huang, Xiaolei, Powell, Douglas, Doblas, Ana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9100498/
https://www.ncbi.nlm.nih.gov/pubmed/35591223
http://dx.doi.org/10.3390/s22093534

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9100498/
https://www.ncbi.nlm.nih.gov/pubmed/35591223
http://dx.doi.org/10.3390/s22093534

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