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Dimensionless study on dynamics of pressure controlled mechanical ventilation system

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Abstract

Dynamics of mechanical ventilation system can be referred in pulmonary diagnostics and treatments. In this paper, to conveniently grasp the essential characteristics of mechanical ventilation system, a dimensionless model of mechanical ventilation system is presented. For the validation of the mathematical model, a prototype mechanical ventilation system of a lung simulator is proposed. Through the simulation and experimental studies on the dimensionless dynamics of the mechanical ventilation system, firstly, the mathematical model is proved to be authentic and reliable. Secondly, the dimensionless dynamics of the mechanical ventilation system are obtained. Last, the influences of key parameters on the dimensionless dynamics of the mechanical ventilation system are illustrated. The study provides a novel method to study the dynamic of mechanical ventilation system, which can be referred in the respiratory diagnostics and treatment.

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References

  1. F. T. Tehrani, A control system for mechanical ventilation of passive and active subjects, Journal of Computer Methods and Programs in Biomedicine, 110 (2013) 511–518.

    Article  Google Scholar 

  2. S. P. Pilbeam and J. M. Cairo, Mechanical ventilation, physiological and clinical application, fourth ed., Mosby Elsevier, St. Louis (2006).

    Google Scholar 

  3. R. L. Chatburn, Classification of ventilator modes, Update and proposal for implementation, Respiratory Care, 52 (2007) 301–323.

    Google Scholar 

  4. A. Rajagiri, B. Diong, M. Goldman and H. Nazeran, Can asthma in children be detected by the estimated parameter values of the augmented RIC model?, Proceedings of Conference of IEEE Eng. Med. Biol. Soc., 1 (2006) 5595–5598.

    Article  Google Scholar 

  5. C. Ionescu, E. Derom and R. De Keyser, Assessment of respiratory mechanical properties with constant-phase models in healthy and COPD lungs, Computers in Methods Programs Biomed., 97 (1) (2010) 78–85.

    Article  Google Scholar 

  6. J. Chmielecki et al., Optimization of dosing for EGFR-mutant non-small cell lung cancer with evolutionary cancer modeling, Sci. Transl. Med., 3 (90) (2011) 90ra59.

    Article  Google Scholar 

  7. H. Koc et al., The role of mathematical modeling in VOC analysis using isoprene as a prototypic example, J. Breath Res. report and papers, 5 (2011) http://dx.doi.org/10.1088/1752-7155/5/3/037102.

    Google Scholar 

  8. J. Szaleniec, J. Skladzien, R. Tadeusiewicz, K. Oles, M. Konior and R. Przeklasa, How can an otolaryngologist benet from arti cial neural networks?, Otolaryngol. Pol., 66 (2012) 241–248.

    Article  Google Scholar 

  9. R. Sturm, A computer model for the simulation of ber-cell interaction in the alveolar region of the respiratory tract, Computers in Biology and Medicine, 41 (2011) 565–573.

    Article  MathSciNet  Google Scholar 

  10. G. Avanzolini et al., A new approach for tracking respiratory mechanical parameters in real-time, Annals of Biomedical Engineering, 25 (1997) 154–163.

    Article  Google Scholar 

  11. A. G. Polak and J. Mroczka, Nonlinear model for mechanical ventilation of human lungs, Computers in Biology and Medicine, 36 (2006) 41–58.

    Article  Google Scholar 

  12. R. Grzegorz and J. Jacek, A new approach to modeling of selected human respiratory system diseases, directed to computer simulations, Computers in Biology and Medicine, 43 (2013) 1606–1613.

    Article  Google Scholar 

  13. W. Tomalak, Wybrane aspekty badania mechaniki oddychania i modelowania systemu oddechowego przy uzyciu techniki oscylacji wymuszonych, Sc.D. Dissertation (1998) IGiCP.ZP; Rabka.

    Google Scholar 

  14. J. Eyles and R. Pimmel, Estimating respiratory mechanical parameters in parallel compartment models, IEEE Transations on Biomed. Engineering, 4 (1981) 313–317.

    Article  Google Scholar 

  15. B. Diong, M. Goldman and H. Nazeran, Respiratory impedance values in adults are relatively insensitive to mead model lung compliance and chest wall compliance parameters, Proceedings of IFMBE, 32 (2010) 201–203.

    Article  Google Scholar 

  16. M. P. Vassiliou et al., Volume and flow dependence of respiratory mechanics in mechanically ventilated COPD patients, Journal of Respiratory Physiology & Neurobiology, 135 (2003) 87–96.

    Article  Google Scholar 

  17. L. Robert, Computer control of mechanical ventilation, Respiratory Care, 49 (5) (2004) 507–515.

    Google Scholar 

  18. J. X. Brunner, History and Principles of Closed-Loop Control Applied to Mechanical Ventilation, Hamilton Medical AG, Rhazuns (2002).

    Google Scholar 

  19. M. Borrello, Modeling and control of systems for critical care ventilation, Proceeding of the 2005 American control conference, Portland, OR, USA (2005) 2166–2180.

    Google Scholar 

  20. Y. Shi and M. Cai, Working characteristics of two kinds of air-driven boosters, Journal of Energy Conversion and Management, 52 (2011) 3399–3407.

    Article  Google Scholar 

  21. M. Cai, K. Kawashima and T. Kagawa, Power assessment of flowing compressed sir, Journal of Fluids Engineering, Transactions of the ASME, 128 (2) (2006) 402–405.

    Article  Google Scholar 

  22. Y. Shi et al., Pressure dynamic characteristics of pressure controlled ventilation system of a lung simulator[J], Computational and mathematical methods in medicine (2014).

    Google Scholar 

  23. Y. Shi et al., Modelling and simulation of volume controlled mechanical ventilation system[J], Mathematical Problems in Engineering (2014).

    Google Scholar 

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Authors and Affiliations

  1. School of Automation Science and Electrical Engineering, Beihang University, Beijing, 100191, China

    Yan Shi, Jinglong Niu, Maolin Cai & Weiqing Xu

  2. Department of Mechanical Engineering, University of Bath, Bath, BA2 7AY, UK

    Yan Shi

Authors
  1. Yan Shi
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  2. Jinglong Niu
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  3. Maolin Cai
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  4. Weiqing Xu
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Corresponding author

Correspondence to Weiqing Xu.

Additional information

Recommended by Editor Yeon June Kang

Yan Shi is a lecture of School of Automation Science and Electrical Engineering, Beihang University, Beijing, China. He received his doctor degree in mechanical engineering from Beihang University. His research interests include intelligent mechanical devices and energy-saving technologies of pneumatic system.

Weiqing Xu is a post doctor of School of Automation Science and Electrical Engineering, Beihang University, Beijing, China. He received his doctor degree in mechanical engineering from Beihang University. His research interests include intelligent mechanical devices and high efficient compressed air energy storage technologies.

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Shi, Y., Niu, J., Cai, M. et al. Dimensionless study on dynamics of pressure controlled mechanical ventilation system. J Mech Sci Technol 29, 431–439 (2015). https://doi.org/10.1007/s12206-015-0101-6

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  • DOI: https://doi.org/10.1007/s12206-015-0101-6

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