Global models for patient-ventilator interactions in noninvasive ventilation with asynchronies

Computers in Biology and Medicine

Volumn 41, Issue 5, 2011, Pages 253-264

  Rodrigues, G G ^a   Aguirre, L A ^b   Cuvelier, A ^d   Muir, J F ^d   Letellier, C ^c  

^a CENTRO FEDERAL DE EDUCAÇÃO TECNOLÓGICA DE MINAS GERAIS   (Brazil)

^b FEDERAL UNIVERSITY OF MINAS GERAIS   (Brazil)

^c UNIVERSITÉ DE ROUEN   (France)

^d ROUEN UNIVERSITY HOSPITAL   (France)

Author keywords

Global modeling; Noninvasive ventilation; Patient ventilator interaction

Indexed keywords

ASYNCHRONY; AUTONOMOUS MODELS; BLOOD OXYGENATION; CLINICAL PROCEDURE; DATA-DRIVEN MODELING; GLOBAL MODELING; GLOBAL MODELS; INPUT-OUTPUT; NON-LINEARITY; NONINVASIVE VENTILATION; PATIENT-VENTILATOR INTERACTION; RESPIRATORY FAILURE; SPONTANEOUS BREATHING; WORK OF BREATHINGS;

OXYGENATION; TIME SERIES;

VENTILATION;

ARTICLE; CHRONIC RESPIRATORY FAILURE; CLINICAL ARTICLE; CONTROLLED STUDY; FEMALE; HUMAN; LUNG VENTILATION; MALE; NONINVASIVE VENTILATION; PRESSURE MEASUREMENT; PRIORITY JOURNAL; RESPIRATORY AIRFLOW;

ALGORITHMS; BLOOD GAS ANALYSIS; BODY MASS INDEX; CLUSTER ANALYSIS; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; COMPUTERS; FEMALE; HUMANS; MALE; MODELS, THEORETICAL; MONITORING, PHYSIOLOGIC; NORMAL DISTRIBUTION; PRESSURE; REGRESSION ANALYSIS; SOFTWARE; VENTILATORS, MECHANICAL;

EID: 79955034697     PISSN: 00104825     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compbiomed.2011.02.009     Document Type: Article

References (34)

1. Georgopoulos D., Prinianakis G., Kondili E. Bedside waveforms interpretation as a tool to identify patient-ventilator asynchronies. Intensive Care Medicine 2006, 32:34-47.
2. Vignaux L., Vargas F., Roeseler J., Tassaux D., Thille A.W., Kossowsky M.P., Brochard L., Jolliet P. Patient-ventilator asynchrony during non-invasive ventilation for acute respiratory failure: a multicenter study. Intensive Care Medicine 2009, 35:840-846.
3. Fanfulla F., Taurino A.E., D'Artavilla Lupo N., Trentin R., D'Ambrosio C., Nava S. Effect of sleep on patient/ventilator asynchrony in patients undergoing chronic non-invasive mechanical ventilation. Respiratory Medicine 2007, 101:1702-1707.
4. H. Rabarimanantsoa-Jamous, Qualité des interactions patient-ventilateur en ventilation noninvasive nocturne, Ph.D. Thesis, Rouen University, 2008.
5. Rabarimanantsoa H., Achour L., Letellier C., Cuvelier A., Muir J.-F. Recurrence plots and Shannon entropy for a dynamical analysis of asynchronisms in noninvasive mechanical ventilation. Chaos 2007, 17:013115-1-013115-10.
6. R. Naeck, D. Bounoiare, U.S. Freitas, H. Rabarimanantsoa, A. Portmann, F. Portier, A. Cuvelier, J.-F. Muir, C. Letellier, Dynamics underlying patient-ventilator interactions during nocturnal noninvasive ventilation, International Journal of Bifurcation & Chaos, submitted for publication.
7. Farmer J.D., Sidorowitch J.J. Predicting chaotic time series. Physical Review Letters 1987, 59(8):845-848.
8. Brown R., Rulkov N.F., Tracy E.R. Modeling and synchronizing chaotic systems from time-series data. Physical Review E 1994, 49(5):3784-3800.
9. Cao L., Mees A., Judd K. Dynamics from multivariate time series. Physica D 1998, 121:75-88.
10. Aguirre L.A., Letellier C. Modeling nonlinear dynamics and chaos: a review. Mathematical Problems in Engineering 2009, 2009:238960.
11. Aguirre L.A., Souza A.V.P. Stability analysis of sleep apnea time series using identified models: a case study. Computers in Biology and Medicine 2004, 34:241-257.
12. Maquet J., Letellier C., Aguirre L.A. Global models from the Canadian lynx cycles as a first evidence for chaos in real ecosystems. Journal of Mathematical Biology 2007, 55(1):21-39.
13. Small M., Judd K. Comparisons of new nonlinear modeling techniques with applications to infant respiration. Physica D 1998, 117:283-298.
14. Letellier C., Aguirre L.A., Freitas U.S. Frequently asked questions about global modeling. Chaos 2009, 19:023103-1-023103-16.
15. Billings S.A., Chen S. Representation of non-linear systems: the NARMAX model. International Journal of Control 1989, 49(3):1013-1032.
16. Mackey M., Glass L. Oscillations and chaos in physiological control systems. Science 1977, 197(4300):287-289.
17. Hong X., Mitchell R.J., Chen S., Harris C.J., Li K., Irwin G.W. Model selection approaches for non-linear system identification: a review. International Journal in Systems Science 2008, 39:925-946.
18. M.J.L. Orr, Introduction to radial basis function networks, Technical Report, Centre for Cognitive Science, Edinburgh University, 1996.
19. Mees A.I., Jackson M.F., Chua L.O. Device modeling by radial basis functions. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications 1992, 39(1):19-27.
20. Haykin S. Neural Networks: A Comprehensive Foundation 1999, Prentice Hall, Upper Saddle River. second ed.
21. Chen S., Cowan C.F.N., Grant P.M. Orthogonal least squares algorithm for radial basis function networks. IEEE Transactions on Neural Networks 1991, 2(2):302-309.
22. Drioli C., Rocchesso D. Orthogonal least squares algorithm for the approximation of a map and its derivatives with an RBF network. Signal Processing 2003, 83:283-296.
23. Karayiannis N.B., Mi G.W. Growing radial basis neural networks: merging supervised and unsupervised learning with network growth techniques. IEEE Transactions on Neural Networks 1997, 8(6):1492-1506.
24. Billings S.A., Wei H.-L., Balikhin M.A. Generalized multiscale radial basis function networks. Neural Networks 2007, 20:1081-1094.
25. M.J.L. Orr, Optimising the widths of radial basis functions, in: Proceedings of the Vth Brazilian Symposium on Neural Networks.
26. Aguirre L.A., Furtado E.C., TÔrres L.A.B. Evaluation of dynamical models: dissipative synchronization and other techniques. Physical Review E 2006, 74:066203-1-066203-16.
27. Korenberg M., Billings S.A., Liu Y.P., McIlroy P.J. Orthogonal parameter estimation algorithm for non-linear stochastic systems. International Journal of Control 1988, 48(1):193-210.
28. Billings S.A., Chen S., Korenberg M. Identification of MIMO non-linear systems using a forward-regression orthogonal estimator. International Journal of Control 1989, 49(6):2157-2189.
29. Chen S., Billings S.A., Luo W. Orthogonal least squares methods and their application to non-linear system identification. International Journal of Control 1989, 50(5):1873-1896.
30. Achour L., Letellier C., Cuvelier A., Vérin E., Muir J.-F. Asynchrony and cyclic variability in pressure support noninvasive ventilation. Computers in Biology and Medicine 2007, 37(9):1308-1320.
31. U.S. Freitas, Caractérisation des cycles ventilatoires, Patent submission # 1000062473, October 2009.
32. Wysocki M., Fiamma M., Straus C., Poon C.-S., Similowski T. Chaotic dynamics of resting ventilatory flow in humans assessed through noise titration. Respiratory Physiology and Neurobiology 2006, 153:54-65.
33. M.J.L. Orr, MATLAB routines for subset selection and ridge regression in linear neural networks, Technical Report, Centre for Cognitive Science, Edinburgh University, 1996. http://anc.ed.ac.uk/rbf/rbf.html.
34. Aguirre L.A., Correa M.V., Cassini C.C.S. Nonlinearities in NARX polynomial models: representation and estimation. IEE Proceedings: Control Theory and Applications 2002, 149(4):343-348.