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Simultaneous Parameter and Input Estimation of a Respiratory Mechanics Model

机译:呼吸力学模型的同时参数和输入估计

摘要

Real-time noninvasive estimation of respiratory mechanics in spontaneously breathing patients is still an open problem in the field of critical care. Even assuming that the system is a simplistic first-order single-compartment model, the presence of unmeasured patient effort still makes the problem complex since both the parameters and part of the input are unknown. This paper presents an approach to overcome the underdetermined nature of the mathematical problem by infusing physiological knowledge into the estimation process and using it to construct an optimization problem subject to physiological constraints. As it relies only on measurements available on standard ventilators, namely the flow and pressure at the patient’s airway opening, the approach is noninvasive. Additionally, breath by breath, it continually provides estimates of the patient respiratory resistance and elastance as well as of the muscle effort waveform without requiring maneuvers that would interfere with the desired ventilation pattern.
机译:自发呼吸患者呼吸力学的实时无创评估仍然是重症监护领域的一个悬而未决的问题。即使假设系统是简单的一阶单室模型,由于参数和输入的一部分都是未知的,无法衡量的患者工作量的存在仍然使问题变得复杂。本文提出了一种通过将生理知识注入估计过程中并利用其构造受生理约束的优化问题来克服数学问题的不确定性的方法。由于它仅依赖于标准呼吸机上的可用测量值,即患者气道开口处的流量和压力,因此该方法是无创的。此外,通过呼吸,它可以连续提供患者呼吸阻力和弹性的估计值,以及肌肉力量波形的估计值,而无需进行会干扰所需通气模式的操作。

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