Development of a Noninvasive Blood Glucose Monitoring System Prototype: Pilot Study.

Valero, Maria; Pola, Priyanka; Falaiye, Oluwaseyi; Ingram, Katherine H; Zhao, Liang; Shahriar, Hossain; Ahamed, Sheikh Iqbal

Valero, Maria; Pola, Priyanka; Falaiye, Oluwaseyi; Ingram, Katherine H; Zhao, Liang; Shahriar, Hossain; Ahamed, Sheikh Iqbal.

Afiliação

Valero M; Department of Information Technology, Kennesaw State University, Marietta, GA, United States.
Pola P; Department of Information Technology, Kennesaw State University, Marietta, GA, United States.
Falaiye O; Department of Software Engineering and Game Development, Kennesaw State University, Marietta, GA, United States.
Ingram KH; Department of Exercise Science and Sport Management, Kennesaw State University, Kennesaw, GA, United States.
Zhao L; Department of Information Technology, Kennesaw State University, Marietta, GA, United States.
Shahriar H; Department of Information Technology, Kennesaw State University, Marietta, GA, United States.
Ahamed SI; Department of Computer Science, Marquette University, Milwaukee, WI, United States.

JMIR Form Res ; 6(8): e38664, 2022 Aug 26.

Article em En | MEDLINE | ID: mdl-36018623

Palavras-chave

deep learning; diabetes; glucose concentration; glucose monitoring; machine learning; noninvasive monitoring; optical sensors

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: JMIR Form Res Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

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