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What Does a first order model Tell Us about PEEP Wave Maneuvers?

Journal of Biomedical Science and Engineering 2017年第5期10卷 66-75页

作者： B.Laufer J.Kretschmer P.D.Docherty Y.S.Chiew K.Moller Institute of Technical Medicine Furtwangen UniversityVillingen-SchwenningenGermany Department of Mechanical Engineering University of CanterburyChristchurchNew Zealand School of Engineering Monash University MalaysiaBandar SunwayMalaysia

Patients with acute respiratory distress syndrome (ARDS) are currently treated with a lung protective ventilation strategy and the application of positive end-expiratory pressure (PEEP), sometimes in combination with recruitment maneuvers. In this study, the respiratory system elastance and airway resistance of each breath before, during and after a specific recruitment maneuver (PEEP wave maneuver) were analyzed in two patient groups, ARDS and control group. A reduction of elastance after the maneuver was observed in ARDS patients. In addition, only healthy lungs exhibited a reduction of the elastance during the course of the maneuver, while the lungs of ARDS patients didn’t show that reduction of elastance. The capability of PEEP wave maneuvers to improve lung ventilation was shown and the dynamic behavior of the elastance after the maneuver was illustrated. Healthy lungs adapt faster to changes in mechanical ventilation than the lungs of ARDS patients.

关键词： ARDS Positive End-Expiratory Pressure Recruitment Maneuvers first order model Lung Mechanics

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A New Lung Mechanics model and Its Evaluation with Clinical Data

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Journal of Biomedical Science and Engineering 2016年第10期9卷 107-115页

作者： Manjunath Jayaramaiah Bernhard Laufer Jörn Kretschmer Knut Möller Institute of Technical Medicine (ITeM) Hochschule Furtwangen University Furtwangen Germany

Acute Respiratory Distress Syndrome (ARDS) is a major cause of morbidity and has a high rate of mortality. ARDS patients in the intensive care unit (ICU) require mechan-ical ventilation (MV) for breathing support, but inappropriate settings of MV can lead to ventilator induced lung injury (VILI). Those complications may be avoided by carefully optimizing ventilation parameters through model-based approaches. In this study we introduced a new model of lung mechanics (mNARX) which is a variation of the NARX model by Langdon et al. A multivariate process was undertaken to deter-mine the optimal parameters of the mNARX model and hence, the final structure of the model fit 25 patient data sets and successfully described all parts of the breathing cycle. The model was highly successful in predicting missing data and showed minimal error. Thus, this model can be used by the clinicians to find the optimal patient specific ventilator settings.

关键词： Acute Respiratory Distress Syndrome Ventilator Induced Lung Injury Non-Linear Autoregressive model first order model Mechanical Ventilation

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