Classifier design for patients on weaning process
Keywords:
Fuzzy logic classifier, K-Nearest neighbor classifier, mechanical ventilation, principal component analysis, wavelet transform.
Abstract
The mechanical ventilation (MV) is a therapeutic strategy to mechanically assist or replace spontaneous breathing. With the objective of developing a software support for doctors was performed a study of respiratory signals using the discrete wavelet transform to determine the descriptors to indicate whether the patient can be disconnected from the mechanical ventilator. To reduce the dimensionality of the system was performed a principal component analysis (PCA), establishing three variables optimal, which are the inputs to the classifiers that were analyzed in the article: K-Nearest Neighbor and fuzzy logic.
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References
[1] J. F. McConville, J. P. Kress, “Weaning patients from the ventilator,” The new England Journal of Medicine, vol. 367, pp. 2233-9, 2012.
[2] A. Esteban, F. Frutos Vivar, A. Muriel, N. D. Ferguson, O. Peñuelas et al., “Evolution of mortality over time in patients receiving mechanical ventilation”. American Journal of Respiratory and Critical Care Medicine, vol. 188, no. 2, 2013.
[3] J. F. McConville, J. P. Kress, “Weaning patients from the ventilator,” New England Journal of Medicine, vol. 367, no. 23, pp. 2233-2239, 2012.
[4] G. Benchetrit, “Breathing pattern in humans: diversity and individuality,” Respiration Physiology, vol. 122, pp. 123-129, 2000.
[5] P. Caminal, L. Domingo, B.F. Giraldo, M. Vallverdú, S. Benito, G. Vázquez, D. Kaplan, “Variability analysis of the respiratory volume based on nonlinear prediction methods,” Medical & Biological Engineering & Computing, vol. 42, pp. 86-91, 2004.
[6] M. J. Tobin, M.J. Mador, S.M. Guenter, R.F. Lodato, M.A. Sackner, “Variability of resting respiratory center drive and timing in healthy subjects,” J. Journal Applied Physiology, vol. 65, pp. 309-317, 1988.
[7] E. N. Bruce, “Measures of respiratory pattern variability, Bioengineering approaches to pulmonary physiology and medicine,” Plenum Press, pp. 149-160, 1996.
[8] M. C. Khoo, “Determinants of ventilatory instability and variability,” Respiratory physiology, vol. 122, pp. 167-182, 2000.
[9] J. A. Chaparro, B. F. Giraldo, P. Caminal, S. Benito, “Analysis of the respiratory pattern variability of patients in weaning process using autoregressive modeling techniques,” Engineering in Medicine and Biology Society, EMBC, 2011.
[10] B. F. Giraldo, B. W. Gaspar, P. Caminal, S. Benito, “Analysis of roots in ARMA model for the classification of patients on weaning trials,” Engineering in Medicine and Biology Society, EMBC, 2012.
[11] Y. Hao-Yung. “Using support vector machine to construct a predictive model for clinical decision-making of ventilation weaning,” Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence).
[12] B. Giraldo, A. Garde, C. Arizmendi, R. Jane, S. Benito, I. Díaz, D. Ballesteros, “Support vector machine classification applied on weaning trials patients,” Engineering in Medicine and Biology Society, 2006. EMBS ‘06. 28th Annual International Conference of the IEEE.
[13] B. Giraldo, C. Arizmendi, E. Romero, R. Alquezar, P. Caminal, S. Benito, D. Ballesteros, “Patients on weaning trials from mechanical ventilation classified with neural networks and feature selection,” Engineering in Medicine and Biology Society, 2006. EMBS ‘06. 28th Annual International Conference of the IEEE.
[14] C. Arizmendi, E. Romero, R. Alquezar, P. Caminal, I. Díaz, S. Benito, B. F. Giraldo, “Data mining of patients on weaning trials from mechanical ventilation using cluster analysis and neural networks,” Engineering in Medicine and Biology Society, 2009. EMBC 2009.
[15] P. Caminal, B. F. Giraldo, M. Vallverdú, S. Benito, R. Schiroeder, A. Voss, “Simbolic dynamic analysis of relations between cardiac and breathing cycles in patients on weaning trials,” Annals of Biomedical Engineering, vol. 38, no. 8, August, 2010, pp. 2542-2552.
[16] L. S. Correa, E. Laciar, B. F. Giraldo, A. Torres, “Multiparameter analysis of ECG and respiratory flow signals to identify success of patients on weaning trials,” 32nd Annual International Conference of the IEEE EMBS, 2010.
[17] A. Arcentales, B. F. Giraldo, P. Caminal, S. Benito, A. Voss, “Recurrence quantification analysis of heart rate variablility and respiratory flow series in patients on weaning trials,” 33rd Annual International Conference of the IEEE EMBS, 2011.
[2] A. Esteban, F. Frutos Vivar, A. Muriel, N. D. Ferguson, O. Peñuelas et al., “Evolution of mortality over time in patients receiving mechanical ventilation”. American Journal of Respiratory and Critical Care Medicine, vol. 188, no. 2, 2013.
[3] J. F. McConville, J. P. Kress, “Weaning patients from the ventilator,” New England Journal of Medicine, vol. 367, no. 23, pp. 2233-2239, 2012.
[4] G. Benchetrit, “Breathing pattern in humans: diversity and individuality,” Respiration Physiology, vol. 122, pp. 123-129, 2000.
[5] P. Caminal, L. Domingo, B.F. Giraldo, M. Vallverdú, S. Benito, G. Vázquez, D. Kaplan, “Variability analysis of the respiratory volume based on nonlinear prediction methods,” Medical & Biological Engineering & Computing, vol. 42, pp. 86-91, 2004.
[6] M. J. Tobin, M.J. Mador, S.M. Guenter, R.F. Lodato, M.A. Sackner, “Variability of resting respiratory center drive and timing in healthy subjects,” J. Journal Applied Physiology, vol. 65, pp. 309-317, 1988.
[7] E. N. Bruce, “Measures of respiratory pattern variability, Bioengineering approaches to pulmonary physiology and medicine,” Plenum Press, pp. 149-160, 1996.
[8] M. C. Khoo, “Determinants of ventilatory instability and variability,” Respiratory physiology, vol. 122, pp. 167-182, 2000.
[9] J. A. Chaparro, B. F. Giraldo, P. Caminal, S. Benito, “Analysis of the respiratory pattern variability of patients in weaning process using autoregressive modeling techniques,” Engineering in Medicine and Biology Society, EMBC, 2011.
[10] B. F. Giraldo, B. W. Gaspar, P. Caminal, S. Benito, “Analysis of roots in ARMA model for the classification of patients on weaning trials,” Engineering in Medicine and Biology Society, EMBC, 2012.
[11] Y. Hao-Yung. “Using support vector machine to construct a predictive model for clinical decision-making of ventilation weaning,” Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence).
[12] B. Giraldo, A. Garde, C. Arizmendi, R. Jane, S. Benito, I. Díaz, D. Ballesteros, “Support vector machine classification applied on weaning trials patients,” Engineering in Medicine and Biology Society, 2006. EMBS ‘06. 28th Annual International Conference of the IEEE.
[13] B. Giraldo, C. Arizmendi, E. Romero, R. Alquezar, P. Caminal, S. Benito, D. Ballesteros, “Patients on weaning trials from mechanical ventilation classified with neural networks and feature selection,” Engineering in Medicine and Biology Society, 2006. EMBS ‘06. 28th Annual International Conference of the IEEE.
[14] C. Arizmendi, E. Romero, R. Alquezar, P. Caminal, I. Díaz, S. Benito, B. F. Giraldo, “Data mining of patients on weaning trials from mechanical ventilation using cluster analysis and neural networks,” Engineering in Medicine and Biology Society, 2009. EMBC 2009.
[15] P. Caminal, B. F. Giraldo, M. Vallverdú, S. Benito, R. Schiroeder, A. Voss, “Simbolic dynamic analysis of relations between cardiac and breathing cycles in patients on weaning trials,” Annals of Biomedical Engineering, vol. 38, no. 8, August, 2010, pp. 2542-2552.
[16] L. S. Correa, E. Laciar, B. F. Giraldo, A. Torres, “Multiparameter analysis of ECG and respiratory flow signals to identify success of patients on weaning trials,” 32nd Annual International Conference of the IEEE EMBS, 2010.
[17] A. Arcentales, B. F. Giraldo, P. Caminal, S. Benito, A. Voss, “Recurrence quantification analysis of heart rate variablility and respiratory flow series in patients on weaning trials,” 33rd Annual International Conference of the IEEE EMBS, 2011.
Published
2015-11-06
How to Cite
González-Acevedo, H., Giraldo-Giraldo, B., & Arizmendi-Pereira, C. (2015). Classifier design for patients on weaning process. ITECKNE, 12(2), 131-137. https://doi.org/https://doi.org/10.15332/iteckne.v12i2.1239
Issue
Section
Research and Innovation Articles
