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Mechanistic Assessment of Cardiovascular State Informed by Vibroacoustic Sensors.
Zare, Ali; Wittrup, Emily; Najarian, Kayvan.
Afiliación
  • Zare A; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48103, USA.
  • Wittrup E; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48103, USA.
  • Najarian K; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48103, USA.
Sensors (Basel) ; 24(7)2024 Mar 29.
Article en En | MEDLINE | ID: mdl-38610400
ABSTRACT
Monitoring blood pressure, a parameter closely related to cardiovascular activity, can help predict imminent cardiovascular events. In this paper, a novel method is proposed to customize an existing mechanistic model of the cardiovascular system through feature extraction from cardiopulmonary acoustic signals to estimate blood pressure using artificial intelligence. As various factors, such as drug consumption, can alter the biomechanical properties of the cardiovascular system, the proposed method seeks to personalize the mechanistic model using information extracted from vibroacoustic sensors. Simulation results for the proposed approach are evaluated by calculating the error in blood pressure estimates compared to ground truth arterial line measurements, with the results showing promise for this method.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Sistema Cardiovascular Idioma: En Revista: Sensors (Basel) Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Sistema Cardiovascular Idioma: En Revista: Sensors (Basel) Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Suiza