Resonantly Coupled High-Efficiency Sensors for Assessment of Ventricular Chamber Size for Autonomous Control of Left Ventricular Assist Device.
ASAIO J
; 69(1): 50-58, 2023 01 01.
Article
en En
| MEDLINE
| ID: mdl-36346948
Current left ventricular assist devices (LVADs) are set to a fixed rpm and are unable to adjust to physiological demands irrespective of preload or afterload. Autonomous control of LVADs has the potential to reduce septal shift, preserve right ventricle function, and meet physiological demands. A highly innovative resonantly coupled regimen is presented which can achieve this goal. We introduce sensors based on a highly sensitive relationship between transmission coefficient and spatial separation in a resonantly coupled regimen. This relationship represents a polynomial regression. A regimen of an apical sensor and multiple outflow sensors is investigated. A range of separations varying from 50-200 mm was systematically investigated. These ranges consider anatomical & physiological variation(s) in cardiac chamber size. Validation was obtained in porcine heart preparation. The polynomial regression model predicted distance between the sensors with a mean absolute percentage error of 0.77%, 1.07%, and 5.75% for the three putative positions of the outflow sensors and apical sensor when compared with experimental results. A high degree of accuracy (95%) between the predicted and observed distance was obtained. Continuous measurements were done over 90 days to examine drift, with no statistically detectable change in measurements over million sampling cycles. We have demonstrated a reliable sensor methodology without drift for assessing ventricular chamber size in an LVAD setup. This has the potential to allow autonomous control of LVAD based on ventricular chamber size to address some of the adverse events.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Corazón Auxiliar
/
Insuficiencia Cardíaca
Tipo de estudio:
Prognostic_studies
Límite:
Animals
Idioma:
En
Revista:
ASAIO J
Asunto de la revista:
TRANSPLANTE
Año:
2023
Tipo del documento:
Article
Pais de publicación:
Estados Unidos