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Optimising low-energy defibrillation in 2D cardiac tissue with a genetic algorithm
Sequences of low-energy electrical pulses can effectively terminate ventricular fibrillation (VF) and avoid the side effects of conventional high-energy electrical defibrillation shocks, including tissue damage, traumatic pain, and worsening of prognosis. However, the systematic optimisation of sequ...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10406519/ https://www.ncbi.nlm.nih.gov/pubmed/37555132 http://dx.doi.org/10.3389/fnetp.2023.1172454 |
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author | Aron, Marcel Lilienkamp, Thomas Luther, Stefan Parlitz, Ulrich |
author_facet | Aron, Marcel Lilienkamp, Thomas Luther, Stefan Parlitz, Ulrich |
author_sort | Aron, Marcel |
collection | PubMed |
description | Sequences of low-energy electrical pulses can effectively terminate ventricular fibrillation (VF) and avoid the side effects of conventional high-energy electrical defibrillation shocks, including tissue damage, traumatic pain, and worsening of prognosis. However, the systematic optimisation of sequences of low-energy pulses remains a major challenge. Using 2D simulations of homogeneous cardiac tissue and a genetic algorithm, we demonstrate the optimisation of sequences with non-uniform pulse energies and time intervals between consecutive pulses for efficient VF termination. We further identify model-dependent reductions of total pacing energy ranging from ∼4% to ∼80% compared to reference adaptive-deceleration pacing (ADP) protocols of equal success rate (100%). |
format | Online Article Text |
id | pubmed-10406519 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104065192023-08-08 Optimising low-energy defibrillation in 2D cardiac tissue with a genetic algorithm Aron, Marcel Lilienkamp, Thomas Luther, Stefan Parlitz, Ulrich Front Netw Physiol Network Physiology Sequences of low-energy electrical pulses can effectively terminate ventricular fibrillation (VF) and avoid the side effects of conventional high-energy electrical defibrillation shocks, including tissue damage, traumatic pain, and worsening of prognosis. However, the systematic optimisation of sequences of low-energy pulses remains a major challenge. Using 2D simulations of homogeneous cardiac tissue and a genetic algorithm, we demonstrate the optimisation of sequences with non-uniform pulse energies and time intervals between consecutive pulses for efficient VF termination. We further identify model-dependent reductions of total pacing energy ranging from ∼4% to ∼80% compared to reference adaptive-deceleration pacing (ADP) protocols of equal success rate (100%). Frontiers Media S.A. 2023-07-24 /pmc/articles/PMC10406519/ /pubmed/37555132 http://dx.doi.org/10.3389/fnetp.2023.1172454 Text en Copyright © 2023 Aron, Lilienkamp, Luther and Parlitz. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Network Physiology Aron, Marcel Lilienkamp, Thomas Luther, Stefan Parlitz, Ulrich Optimising low-energy defibrillation in 2D cardiac tissue with a genetic algorithm |
title | Optimising low-energy defibrillation in 2D cardiac tissue with a genetic algorithm |
title_full | Optimising low-energy defibrillation in 2D cardiac tissue with a genetic algorithm |
title_fullStr | Optimising low-energy defibrillation in 2D cardiac tissue with a genetic algorithm |
title_full_unstemmed | Optimising low-energy defibrillation in 2D cardiac tissue with a genetic algorithm |
title_short | Optimising low-energy defibrillation in 2D cardiac tissue with a genetic algorithm |
title_sort | optimising low-energy defibrillation in 2d cardiac tissue with a genetic algorithm |
topic | Network Physiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10406519/ https://www.ncbi.nlm.nih.gov/pubmed/37555132 http://dx.doi.org/10.3389/fnetp.2023.1172454 |
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