A closed-loop system for controlling blood oxygen and carbon dioxide levels in mechanically ventilated patients

Fernando, Tyrone; Packer, J.S.; Cade, J. F.

doi:10.1016/0967-0661(95)00146-l

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…Adjustments are made by varying the level of therapeutic settings on the device including fraction of inspired oxygen (FiO 2 ) (Morozoff and Saif, 2008; Pomprapa et al, 2017), tidal volume (Martinoni et al, 2004), and positive end expiratory pressure (Tehrani, 2012; Flechelles et al, 2013). A wide range of controller types have been applied including model predictive controllers (Fernando et al, 1995; Pomprapa et al, 2017), PID and fuzzy controller (Morozoff and Saif, 2008), robust controllers (Sano et al, 1988; Pomprapa et al, 2013), and rule-based expert systems (Fernando et al, 1995).…”

Section: Closed-loop Systems For Mechanical Ventilationmentioning

confidence: 99%

Credibility Evidence for Computational Patient Models Used in the Development of Physiological Closed-Loop Controlled Devices for Critical Care Medicine

et al. 2019

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Physiological closed-loop controlled medical devices automatically adjust therapy delivered to a patient to adjust a measured physiological variable. In critical care scenarios, these types of devices could automate, for example, fluid resuscitation, drug delivery, mechanical ventilation, and/or anesthesia and sedation. Evidence from simulations using computational models of physiological systems can play a crucial role in the development of physiological closed-loop controlled devices; but the utility of this evidence will depend on the credibility of the computational model used. Computational models of physiological systems can be complex with numerous nonlinearities, time-varying properties, and unknown parameters, which leads to challenges in model assessment. Given the wide range of potential uses of computational patient models in the design and evaluation of physiological closed-loop controlled systems, and the varying risks associated with the diverse uses, the specific model as well as the necessary evidence to make a model credible for a use case may vary. In this review, we examine the various uses of computational patient models in the design and evaluation of critical care physiological closed-loop controlled systems (e.g., hemodynamic stability, mechanical ventilation, anesthetic delivery) as well as the types of evidence (e.g., verification, validation, and uncertainty quantification activities) presented to support the model for that use. We then examine and discuss how a credibility assessment framework (American Society of Mechanical Engineers Verification and Validation Subcommittee, V&V 40 Verification and Validation in Computational Modeling of Medical Devices) for medical devices can be applied to computational patient models used to test physiological closed-loop controlled systems.

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