Accuracy of non-invasive cuffless blood pressure in the intensive care unit: Promises and challenges.

Heimark, Sondre; Bøtker-Rasmussen, Kasper Gade; Stepanov, Alexey; Haga, Øyvind Gløersen; Gonzalez, Victor; Seeberg, Trine M; Fadl Elmula, Fadl Elmula M; Waldum-Grevbo, Bård

Heimark, Sondre; Bøtker-Rasmussen, Kasper Gade; Stepanov, Alexey; Haga, Øyvind Gløersen; Gonzalez, Victor; Seeberg, Trine M; Fadl Elmula, Fadl Elmula M; Waldum-Grevbo, Bård.

Afiliação

Heimark S; Department of Nephrology, Oslo University Hospital, Ullevål, Oslo, Norway.
Bøtker-Rasmussen KG; Institute of Clinical Medicine, University of Oslo, Oslo, Norway.
Stepanov A; Aidee Health AS, Oslo, Norway.
Haga ØG; Department of Smart Sensors and Microsystems, SINTEF Digital, Oslo, Norway.
Gonzalez V; Aidee Health AS, Oslo, Norway.
Seeberg TM; Department of Smart Sensors and Microsystems, SINTEF Digital, Oslo, Norway.
Fadl Elmula FEM; Department of Smart Sensors and Microsystems, SINTEF Digital, Oslo, Norway.
Waldum-Grevbo B; Aidee Health AS, Oslo, Norway.

Front Med (Lausanne) ; 10: 1154041, 2023.

Article em En | MEDLINE | ID: mdl-37138759

Palavras-chave

blood pressure; cuffless; intensive care unit; machine learning; pulse arrival time

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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article