A Variable Resistance Respiratory Mechanics Model

Redmond, Daniel P.; Kim, Kyeong Tae; Morton, Sophie E.; Howe, Sarah; Chiew, Yeong Shiong; Chase, J. Geoffrey

doi:10.1016/j.ifacol.2017.08.1533

Cited by 9 publications

(10 citation statements)

References 22 publications

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“…The models mentioned earlier are all cases where the coefficients of the differential equations are constants. In the actual respiratory system, the elasticity E and airway resistance R may be variables rather than constants ( Van Drunen et al, 2014 ; Chiew et al, 2015 ; Redmond et al, 2017 ; Ellwein Fix et al, 2018 ; Marconi and De Lazzari, 2020 ). When the elasticity E changes with V(t), and the resistance R changes with V′(t), based on Eq.…”

Section: Methodsmentioning

confidence: 99%

“…Examples are provided by the single-compartment model ( Bates, 2009 ; Ghafarian et al, 2016 ; Gertler, 2021 ) corresponding to a first-order linear differential system, the two-compartment model ( Bates, 2009 ; Carvalho and Zin, 2011 ; Ghafarian et al, 2016 ) corresponding to a second-order differential system, and the viscoelastic model ( Ganzert et al, 2009 ). Over the last few years, different types of respiratory mechanics models have been put forward, including nonlinear models involving elastance and resistance of the respiratory system ( Chiew et al, 2015 ; Redmond et al, 2017 ; Ellwein Fix et al, 2018 ; Marconi and De Lazzari, 2020 ). These studies generally provide a good theoretical modelling and may be used to simulate the respiratory system.…”

Section: Introductionmentioning

confidence: 99%

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An enhanced respiratory mechanics model based on double-exponential and fractional calculus

Li,

Pei,

Wang

et al. 2023

Front. Physiol.

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We address mathematical modelling of respiratory mechanics and put forward a model based on double-exponential and fractional calculus for parameter estimation, model simulation, and evaluation based on actual data. Our model has been implemented on a publicly available executable code with adjustable parameters, making it suitable for different applications. Our analysis represents the first application of fractional calculus and double-exponential modelling to respiratory mechanics, and allows us to propose a hybrid model fitting experimental data in different ventilation modes. Furthermore, our model can be used to study the mechanical features of the respiratory system, improve the safety of ventilation techniques, reduce ventilation damages, and provide strong support for fast and adaptive determination of ventilation parameters.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An enhanced respiratory mechanics model based on double-exponential and fractional calculus

Li,

Pei,

Wang

et al. 2023

Front. Physiol.

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“…Assumptions: For the purpose of this study, it's assumed that standard resistances of the hose, leak channel, and patient's lungs are known. This is a commonly accepted assumption in several studies within this domain [24][25][26]. By assuming this, it simplifies the modeling process and allows for a focused analysis of control strategies.…”

Section: Figure 1 Schematic Of a Mechanical Ventilation Unitmentioning

confidence: 96%

“…The aim of the control system is to track the measured pressure and make sure that it corresponds to the desired set point, Pr. As a result, the error equation is formulated as follows [24]:…”

Section: Figure 1 Schematic Of a Mechanical Ventilation Unitmentioning

confidence: 99%

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Comparative Analysis of Airflow Regulation in Ventilator Systems Using Various Control Strategies

Shanan,

Kadhim

2023

JESA

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Ventilator designs, pivotal in providing respiratory support to patients, often grapple with performance optimization challenges due to variable patient conditions and intricate mechanical components. This research strives to identify the optimal control strategy that can assure maximal patient safety and efficient ventilator operation. We compared three control strategies: the conventional Proportional-Integral-Derivative (PID) control, the Nonlinear PID control, and the sliding mode control (SMC) equipped with signum function triggers. Our studies underscored the preeminence of SMC in controlling airway pressure, exhibiting a rapid and disturbance-free response. However, while SMC ensured smooth patient airflow in flow rate control, it exhibited a slightly delayed response. The research thus posits SMC as a promising contender, particularly in light of the sophisticated design requirements of contemporary ventilators. Through this investigation, we aim to offer a robust control solution capable of enhancing current ventilator operations to ensure superior patient safety and efficiency.

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