Detection of Hypoglycemia and Hyperglycemia Using Noninvasive Wearable Sensors: ECG and Accelerometry.

Dave, Darpit; Vyas, Kathan; Branan, Kimberly; McKay, Siripoom; DeSalvo, Daniel J; Gutierrez-Osuna, Ricardo; Cote, Gerard L; Erraguntla, Madhav

Dave, Darpit; Vyas, Kathan; Branan, Kimberly; McKay, Siripoom; DeSalvo, Daniel J; Gutierrez-Osuna, Ricardo; Cote, Gerard L; Erraguntla, Madhav.

Afiliação

Dave D; Wm Michael Barnes '64 Department of Industrial and Systems Engineering, Texas A&M University, College Station, TX, USA.
Vyas K; Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA.
Branan K; Department of Biomedical Engineering, Texas A&M University, College Station, TX, USA.
McKay S; Baylor College of Medicine, Houston, TX, USA.
DeSalvo DJ; Texas Children's Hospital Clinical Care Center, Houston, TX, USA.
Gutierrez-Osuna R; Baylor College of Medicine, Houston, TX, USA.
Cote GL; Texas Children's Hospital Clinical Care Center, Houston, TX, USA.
Erraguntla M; Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA.

J Diabetes Sci Technol ; : 19322968221116393, 2022 Aug 04.

Article em En | MEDLINE | ID: mdl-35927975

Palavras-chave

accelerometer data; electrocardiogram (ECG); hyperglycemia; hypoglycemia; noninvasive blood glucose monitoring; quantile regression; random forests

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Revista: J Diabetes Sci Technol Assunto da revista: ENDOCRINOLOGIA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Estados Unidos

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