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Published on: February 13, 2021
Human Hypertension Blood Flow Model Using Fractional Calculus.
Mohamed A Bahloul1, Yasser Aboelkassem2,3, Taous-Meriem Laleg-Kirati1,4
1Computer, Electrical, and Mathematical Sciences, and Engineering Division (CEMSE), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.
This study models blood flow in hypertensive arteries using fractional calculus. The new fractional model accurately reflects arterial changes in hypertension, offering insights into disease progression.
Area of Science:
- Biomedical Engineering
- Cardiovascular Physiology
- Applied Mathematics
Background:
- Hypertension significantly alters human arterial structure and function.
- Accurate modeling of blood flow dynamics is crucial for understanding cardiovascular diseases.
- Traditional models may not fully capture the complex viscoelastic properties of arteries.
Purpose of the Study:
- To develop and validate a novel fractional calculus-based model for blood flow dynamics in hypertensive human arteries.
- To investigate the physiological interpretability of fractional differentiation orders in arterial mechanics.
- To assess the potential of fractional-order modeling in understanding hypertension-induced arterial changes.
Main Methods:
- A five-element lumped parameter arterial Windkessel model was adapted.
- Fractional-order capacitors were employed to represent arterial elasticity.
- The model was validated using data from human hypertensive patients.
Main Results:
- The proposed fractional model demonstrated high flexibility in characterizing the arterial tree network.
- Validation using hypertensive patient data confirmed the model's accuracy.
- The fractional differentiation order showed physiological interpretability.
Conclusions:
- Fractional-order modeling provides a flexible and accurate approach to simulating blood flow in hypertensive arteries.
- This method enhances the understanding of structural and functional arterial modifications in hypertension.
- Fractional calculus offers significant potential for advancing cardiovascular disease research.
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