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Cardiac Active Tension Modeling via Genetic Algorithm-Optimized Fractional Order Systems
Developing a computational model to model cardiac activity has been increasingly important in recent decades. Accurate cell-level active tension modeling for cardiomyocytes is critical to understanding cardiac functionality on a patient-specific basis and developing an effective in-silico cardiac mo...
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| Format: | Thesis |
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AUC Knowledge Fountain
2024
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| _version_ | 1867613422994063360 |
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| access_status_str | Open Access |
| author | Elhamshari, Afnan Khaled |
| author_browse | Elhamshari, Afnan Khaled |
| author_facet | Elhamshari, Afnan Khaled |
| author_sort | Elhamshari, Afnan Khaled |
| collection | Thesis |
| description | Developing a computational model to model cardiac activity has been increasingly important in recent decades. Accurate cell-level active tension modeling for cardiomyocytes is critical to understanding cardiac functionality on a patient-specific basis and developing an effective in-silico cardiac model. However, cell-level models in the literature fail to account for viscoelasticity and inter-patient variations in active tension. This research proposes a genetic algorithm-optimized, fractional order system to model cell-level active tension by extending Land’s state-of-the-art model of cardiac contraction. The model features the (left) Caputo derivative of six state variables that identify the mechanistic origins of viscoelasticity in a myocardial cell in terms of the thin filament, thick filament, and length-dependent interactions. This proposed Caputo Land System (CLS) model is the first of its kind for active tension modeling in cells and demonstrates notable patient-specificity, with smaller mean square errors than the reference model relative to cell-level experiments, promising greater clinical relevance than its counterparts in the literature. |
| format | Thesis |
| id | oai:fount.aucegypt.edu:etds-3215 |
| institution | American University in Cairo (Egypt) |
| last_indexed | 2026-06-10T12:35:54.296Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from AUC Knowledge Fountain — bepress |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | AUC Knowledge Fountain |
| publisherStr | AUC Knowledge Fountain |
| record_format | dspace |
| source_str | AUC Knowledge Fountain — bepress |
| spelling | oai:fount.aucegypt.edu:etds-3215 Cardiac Active Tension Modeling via Genetic Algorithm-Optimized Fractional Order Systems Elhamshari, Afnan Khaled Developing a computational model to model cardiac activity has been increasingly important in recent decades. Accurate cell-level active tension modeling for cardiomyocytes is critical to understanding cardiac functionality on a patient-specific basis and developing an effective in-silico cardiac model. However, cell-level models in the literature fail to account for viscoelasticity and inter-patient variations in active tension. This research proposes a genetic algorithm-optimized, fractional order system to model cell-level active tension by extending Land’s state-of-the-art model of cardiac contraction. The model features the (left) Caputo derivative of six state variables that identify the mechanistic origins of viscoelasticity in a myocardial cell in terms of the thin filament, thick filament, and length-dependent interactions. This proposed Caputo Land System (CLS) model is the first of its kind for active tension modeling in cells and demonstrates notable patient-specificity, with smaller mean square errors than the reference model relative to cell-level experiments, promising greater clinical relevance than its counterparts in the literature. 2024-01-31T08:00:00Z thesis application/pdf https://fount.aucegypt.edu/etds/2173 https://fount.aucegypt.edu/context/etds/article/3215/viewcontent/Thesis_Afnan_Elhamshari.pdf Theses and Dissertations AUC Knowledge Fountain Active tension; Cardiac viscoelasticity; Fractional-order systems; Quick stretch and release experiments; Caputo’s fractional derivatives; Mean Square Error (MSE) Biomechanical Engineering Computational Engineering |
| spellingShingle | Active tension; Cardiac viscoelasticity; Fractional-order systems; Quick stretch and release experiments; Caputo’s fractional derivatives; Mean Square Error (MSE) Biomechanical Engineering Computational Engineering Elhamshari, Afnan Khaled Cardiac Active Tension Modeling via Genetic Algorithm-Optimized Fractional Order Systems |
| title | Cardiac Active Tension Modeling via Genetic Algorithm-Optimized Fractional Order Systems |
| title_full | Cardiac Active Tension Modeling via Genetic Algorithm-Optimized Fractional Order Systems |
| title_fullStr | Cardiac Active Tension Modeling via Genetic Algorithm-Optimized Fractional Order Systems |
| title_full_unstemmed | Cardiac Active Tension Modeling via Genetic Algorithm-Optimized Fractional Order Systems |
| title_short | Cardiac Active Tension Modeling via Genetic Algorithm-Optimized Fractional Order Systems |
| title_sort | cardiac active tension modeling via genetic algorithm optimized fractional order systems |
| topic | Active tension; Cardiac viscoelasticity; Fractional-order systems; Quick stretch and release experiments; Caputo’s fractional derivatives; Mean Square Error (MSE) Biomechanical Engineering Computational Engineering |
| url | https://fount.aucegypt.edu/etds/2173 https://fount.aucegypt.edu/context/etds/article/3215/viewcontent/Thesis_Afnan_Elhamshari.pdf |
| work_keys_str_mv | AT elhamshariafnankhaled cardiacactivetensionmodelingviageneticalgorithmoptimizedfractionalordersystems |