scholarly journals Determination of respiratory gas flow by electrical impedance tomography in an animal model of mechanical ventilation

2014 ◽  
Vol 14 (1) ◽  
Author(s):  
Marc Bodenstein ◽  
Stefan Boehme ◽  
Stephan Bierschock ◽  
Andreas Vogt ◽  
Matthias David ◽  
...  
2020 ◽  
Vol 24 (4) ◽  
pp. 287-292
Author(s):  
Serena Tomasino ◽  
Rosa Sassanelli ◽  
Corrado Marescalco ◽  
Francesco Meroi ◽  
Luigi Vetrugno ◽  
...  

At the end of 2019, a novel coronavirus (COVID-19) was identified as the cause of a cluster of pneumonia cases, with high needs of mechanical ventilation in critically ill patients. It is still unclear whether different types of COVID-19 pneumonia require different ventilator strategies. With electrical impedance tomography (EIT) we evaluated, in real time and bedside, the distribution of ventilation in the different pulmonary regions before, during, and after pronation in COVID-19 respiratory failure. We present a brief literature review of EIT in non-COVID-19 patients and a report of 2 COVID-19 patients: one that did not respond well and another one that improved during and after pronation. EIT might be a useful tool to decide whether prone positioning should or should not be used in COVID-19 pneumonia.


2018 ◽  
Vol 30 (3) ◽  
pp. 481-504 ◽  
Author(s):  
HABIB AMMARI ◽  
FAOUZI TRIKI ◽  
CHUN-HSIANG TSOU

The multifrequency electrical impedance tomography consists in retrieving the conductivity distribution of a sample by injecting a finite number of currents with multiple frequencies. In this paper, we consider the case where the conductivity distribution is piecewise constant, takes a constant value outside a single smooth anomaly, and a frequency dependent function inside the anomaly itself. Using an original spectral decomposition of the solution of the forward conductivity problem in terms of Poincaré variational eigenelements, we retrieve the Cauchy data corresponding to the extreme case of a perfect conductor, and the conductivity profile. We then reconstruct the anomaly from the Cauchy data. The numerical experiments are conducted using gradient descent optimization algorithms.


2020 ◽  
Author(s):  
Ji Qian ◽  
Juan Zhou ◽  
Bao Di ◽  
Yang Liu ◽  
Gang Zhang

Abstract Background Soluble sugar and starch, as carbon sources, directly participate in plant metabolism by providing energy. Conventional determination of plant starch and soluble sugar content usually involves destructive sampling, complicated procedures, and considerable amounts of chemicals and labor. Therefore, there is an urgent need to develop a non-destructive and rapid method for determining plant starch and soluble sugar contents. Electrical impedance tomography (EIT) technology has been used to determine the physiological state and cold resistance of plant tissues. However, so far there have been no reports on the use of EIT for the rapid estimation of soluble sugar and starch contents. Results In this study, EIT was used to obtain reconstructed voltage values and estimate starch and soluble sugar contents in the stems of three Rosa hybrida cultivars during February to May. Stems from two of the cultivars were used for establishing regression models for starch and soluble sugar contents as functions of reconstructed voltage values. The third cultivar was used to test the accuracy of the regression models. The results showed that the reconstructed voltage value significantly correlated with soluble sugar and starch contents. The quadratic regression model was best for determining soluble sugar content and the logarithmic regression model was best for determining starch content. Conclusions Thus, we preliminarily established and verified regression models for estimating soluble sugar and starch contents using reconstructed voltage values of rose stems. These data provide technical support for using EIT to analyze changes in physiological parameters and to rapidly estimate physiological indexes of plants.


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