Weaning from Mechanical Ventilation: a Multimodal Signal Analysis

J. P. Casaseca, M. Martin-Fernandez, C. Alberola-Lopez
IEEE Transactions on Biomedical Engineering
Volume 53, Number 7, Pages 1330-1345
July, 2006

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Abstract

Practitioners' decision for mechanical aid discontinuation is a challenging task that involves a complete knowledge of a great number of clinical parameters, as well as its evolution in time. Recently, an increasing interest on respiratory pattern variability as an extubation readiness indicator has appeared. Reliable assessment of this variability involves a set of signal processing and pattern recognition techniques. This paper presents a suitability analysis of different methods used for breathing pattern complexity assessment. The contribution of this analysis is threefold: 1) to serve as a review of the state of the art on the so-called weaning problem from a signal processing point of view; 2) to provide insight into the applied processing techniques and how they fit into the problem; 3) to propose additional methods and further processing in order to improve breathing pattern regularity assessment and weaning readiness decision. Results on experimental data show that sample entropy outperforms other complexity assessment methods and that multidimensional classification does improve weaning prediction. However, the obtained performance may be objectionable for real clinical practice, a fact that paves the way for a multimodal signal processing framework, including additional high-quality signals and more reliable statistical methods.

Reference

Casaseca JP, Martin-Fernandez M, Alberola-Lopez C. Weaning from mechanical ventilation: a multimodal signal analysis. IEEE Transactions on Biomedical Engineering 2006;53(7):1330-1345.

Bibtex entry

@Article{casasecaTBME06,
  author         = {J. P. Casaseca and M. Martin-Fernandez and C.              
                   Alberola-Lopez},                                            
  title          = {Weaning from Mechanical Ventilation: a Multimodal Signal   
                   Analysis},                                                  
  journal        = {IEEE Transactions on Biomedical Engineering},              
  year           = {2006},                                                     
  volume         = {53},                                                       
  number         = {7},                                                        
  pages          = {1330--1345},                                               
  month          = {July}
}

Grants

TIC2001-3808-C02, TEC2004-06647-C03, FIS PI0-41483, JCYL VA0-75A05, NOE FP6-507609

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