Time-variant left ventricle models for intracardiac impedance analysis
Cardiovascular diseases are a leading cause of mortality worldwide. Thus, critically ill patients require continuous monitoring of cardiovascular indicators, such as the left ventricular volume (LVV). Although continuous hemodynamic monitoring of patients is desirable, due to technical limitations,...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2024-10-01
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| Series: | Journal of Electrical Bioimpedance |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/joeb-2024-0015 |
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| Summary: | Cardiovascular diseases are a leading cause of mortality worldwide. Thus, critically ill patients require continuous monitoring of cardiovascular indicators, such as the left ventricular volume (LVV). Although continuous hemodynamic monitoring of patients is desirable, due to technical limitations, current measurement technologies either require manual intervention of the physician or only provide inaccurate results. Intracardiac impedance measurements are a promising approach for continuous assessment of cardiac function. However, developing and evaluating these methods requires a simulation model of the left ventricle with cardiac motion during an entire cardiac cycle. While many models exist for a fixed ventricle size, to date, no freely available models incorporate time and represent the cardiac motion during a complete cardiac cycle. Therefore, we developed four cardiacmechanical left ventricular models with varying ventricle sizes and complexities. Each model focuses on a different aspect of the geometric shape, thus allowing an isolated analysis of the different influences. This paper presents the development of the models and initial results of the impedance analysis. All measured admittances exhibit a high resemblance for all models and a strong, non-linear correlation with the LVV. A comparison between the models shows how the different geometries affect the impedance. The models, thus, provide a useful basis for the development of LVV estimation algorithms. |
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| ISSN: | 1891-5469 |