Parameter estimation of an artificial respiratory system under mechanical ventilation following a noisy regime
Victor Júnior, Marcus Henrique; Forgiarini Junior, Luiz Alberto; Kinjo, Toru Miyagi; Amato, Marcelo Britto Passos; Yoneyama, Takashi; Tanaka, Harki
http://dx.doi.org/10.1590/2446-4740.0581
Res. Biomed. Eng., vol.31, n4, p.343-351, 2015
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Abstract
Introduction: This work concerns the assessment of a novel system for mechanical ventilation and a parameter estimation method in a bench test. The tested system was based on a commercial mechanical ventilator and a personal computer. A computational routine was developed do drive the mechanical ventilator and a parameter estimation method was utilized to estimate positive end-expiratory pressure, resistance and compliance of the artificial respiratory system. Methods: The computational routine was responsible for establishing connections between devices and controlling them. Parameters such as tidal volume, respiratory rate and others can be set for standard and noisy ventilation regimes. Ventilation tests were performed directly varying parameters in the system. Readings from a calibrated measuring device were the basis for analysis. Adopting a first-order linear model, the parameters could be estimated and the outcomes statistically analysed. Results: Data acquisition was effective in terms of sample frequency and low noise content. After filtering, cycle detection and estimation took place. Statistics of median, mean and standard deviation were calculated, showing consistent matching with adjusted values. Changes in positive end-expiratory pressure statistically imply changes in compliance, but not the opposite. Conclusion: The developed system was satisfactory in terms of clinical parameters. Statistics exhibited consistent relations between adjusted and estimated values, besides precision of the measurements. The system is expected to be used in animals, with a view to better understand the benefits of noisy ventilation, by evaluating the estimated parameters and performing cross relations among blood gas, ultrasonography and electrical impedance tomography.
Keywords
Noisy ventilation, Respiratory care, Mechanical ventilator, Parameter estimation, Compliance, Respiratory system model.
References
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Suki B, Arold SP, Mora R, Lutchen KR, Ingenito EP. Variable tidal volume ventilation improves lung mechanics and gas exchange in a rodent model of acute lung injury. American Journal of Respiratory and Critical Care Medicine. 2002; 165(3):366-71. http://dx.doi.org/10.1164/ajrccm.165.3.2010155. PMid:11818322.
Tustison NJ, Cook TS, Song G, Gee JC. Pulmonary kinematics from image data: a review. Academic Radiology. 2011; 18(4):402-17. http://dx.doi.org/10.1016/j.acra.2010.10.019. PMid:21377592.
Ventmeter. Magnamed [internet]. São Paulo; 2015. [cited 2015 July 22]. Available from: http://www.ventmeter.com.br/.
Victor MH Jr. Implementation and assessment of a novel mechanical ventilatory system following a noisy ventilation regime [dissertation]. São José dos Campos: Instituto Tecnológico de Aeronáutica; 2014.
Zhao Z, Guttmann J, Moller K. Assessment of a volume-dependent dynamic respiratory system compliance in ALI/ARDS by pooling breathing cycles. Physiological Measurement. 2012; 33(8):61-7. http://dx.doi.org/10.1088/0967-3334/33/8/N61. PMid:22828159.
Barr C, Çetinkaya-Rundel M, Diez D. OpenIntro statistics. Verlag: Create Space Independent Publishing Platform; 2012.
Beda A, Spieth PM, Handzsuj T, Pelosi P, Carvalho NC, Koch T, Abreu MG. A novel adaptive control system for noisy pressure-controlled ventilation: a numerical simulation and bench test study. Intensive Care Medicine. 2010; 36(1):164-8. http://dx.doi.org/10.1007/s00134-009-1665-3. PMid:19779696.
Carvalho AR, Zin WA. Respiratory system dynamical mechanical properties: modeling in time and frequency domain. Biophysical Reviews. 2011; 3(2):71-84. http://dx.doi.org/10.1007/s12551-011-0048-5.
Cordioli RL, Akoumianaki E, Brochard L. Nonconventional ventilation techniques. Current Opinion in Critical Care. 2013; 19(1):31-7. http://dx.doi.org/10.1097/MCC.0b013e32835c517d. PMid:23235544.
Diong B, Nazeran H, Nava P, Goldman M. Modelling human respiratory impedance. IEEE Engineering in Medicine and Biology Magazine. 2007; 26(1):48-55. http://dx.doi.org/10.1109/MEMB.2007.289121. PMid:17278772.
Fernández J, Miguelena D, Mulett H, Godoy J, Martinón-Torres F. Adaptive support ventilation: State of the art review. Indian Journal of Critical Care Medicine. 2013; 17(1):16-22. http://dx.doi.org/10.4103/0972-5229.112149. PMid:23833471.
Gama de Abreu M, Spieth PM, Pelosi P, Carvalho AR, Walter C, Schreiber-Ferstl A, Aikele P, Neykova B, Hübler M, Koch T. Noisy pressure support ventilation: A pilot study on a new assisted ventilation mode in experimental lung injury. Critical Care Medicine. 2008; 36(3):818-27. http://dx.doi.org/10.1097/01.CCM.0000299736.55039.3A. PMid:18431269.
Girija G, Raol JR, Singh J. Modelling and parameter estimation of dynamic systems. London: The Institution of Engineering and Technology; 2004.
Kuchnicka K, Maciejewski D. Ventilator-associated lung injury. Anaesthesiology Intensive Therapy. 2013; 45(3):164-70. http://dx.doi.org/10.5603/AIT.2013.0034. PMid:24092514.
Michigan Instruments. Mechanical Lung Simulator Model 5601i [internet]. Michigan; 2015. [cited 2015 July 22]. Available from: http://www.michiganinstruments.com/shop/test-lung-products/item/adult-and-infant.
Mesić S, Babuska R, Hoogsteden H, Verbraak A. Computer-controlled mechanical simulation of the artificially ventilated human respiratory system. IEEE Transactions on Biomedical Engineering. 2003; 50(6):731-43. http://dx.doi.org/10.1109/TBME.2003.812166. PMid:12814240.
Moerer O. Weaning from mechanical ventilation: Which strategies are useful? Anästhesiologie, Intensivmedizin, Notfallmedizin, Schmerztherapie. 2013; 48(10):640-7. PMid:24193691.
Mulqueeny Q, Tassaux D, Vignaux L, Jolliet P, Schindhelm K, Redmond S, Lovell NH. Online estimation of respiratory mechanics in non-invasive pressure support ventilation: a bench model study. In: Proceedings of the 32nd Annual International Conference of the IEEE IEEE Engeneering in Medicine and Biolody Society; 2010; Buenos Aires, Argentina. USA: IEEE; 2010.
Oxymag. Magnamed [internet]. São Paulo; 2015. [cited 2015 July 22]. Available from: http://www.oxymag.com.br.
Saatçi E, Akan A. Respiratory parameter estimation in linear lung models. In: Proceedings of the 30th Annual International IEEE EMBS Conference; 2008 Aug 21-24; Vancouver, Canada. USA: IEEE; 2008. p. 20-4.
Spieth PM, Carvalho AR, Guldner A, Kasper M, Schubert R, Carvalho NC, Beda A, Dassow C, Uhlig S, Koch T, Pelosi P, Gama de Abreu M. Pressure support improves oxygenation and lung protection compared to pressure controlled ventilation and is further improved by random variation of pressure support. Critical Care Medicine. 2011; 39(4):746-55. http://dx.doi.org/10.1097/CCM.0b013e318206bda6. PMid:21263322.
Spieth PM, Carvalho AR, Pelosi P, Hoehn C, Meissner C, Kasper M, Hübler M, von Neindorff M, Dassow C, Barrenschee M, Uhlig S, Koch T, Abreu MG. Variable tidal volumes improve lung protective ventilation strategies in experimental lung injury. American Journal of Respiratory and Critical Care Medicine. 2009a; 179(8):684-93. http://dx.doi.org/10.1164/rccm.200806-975OC. PMid:19151194.
Spieth PM, Carvalho AR, Guldner A, Pelosi P, Kirichuk O, Koch T, Abreu MG. Effects of different levels of pressure support variability in experimental lung injury. Anesthesiology. 2009b; 110(2):342-50. http://dx.doi.org/10.1097/ALN.0b013e318194d06e. PMid:19194161.
Suki B, Arold SP, Mora R, Lutchen KR, Ingenito EP. Variable tidal volume ventilation improves lung mechanics and gas exchange in a rodent model of acute lung injury. American Journal of Respiratory and Critical Care Medicine. 2002; 165(3):366-71. http://dx.doi.org/10.1164/ajrccm.165.3.2010155. PMid:11818322.
Tustison NJ, Cook TS, Song G, Gee JC. Pulmonary kinematics from image data: a review. Academic Radiology. 2011; 18(4):402-17. http://dx.doi.org/10.1016/j.acra.2010.10.019. PMid:21377592.
Ventmeter. Magnamed [internet]. São Paulo; 2015. [cited 2015 July 22]. Available from: http://www.ventmeter.com.br/.
Victor MH Jr. Implementation and assessment of a novel mechanical ventilatory system following a noisy ventilation regime [dissertation]. São José dos Campos: Instituto Tecnológico de Aeronáutica; 2014.
Zhao Z, Guttmann J, Moller K. Assessment of a volume-dependent dynamic respiratory system compliance in ALI/ARDS by pooling breathing cycles. Physiological Measurement. 2012; 33(8):61-7. http://dx.doi.org/10.1088/0967-3334/33/8/N61. PMid:22828159.
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