Methodology for determine the moment of disconnection of patients of the mechanical ventilation using discrete wavelet transform

Author

Gonzalez, H. ; Acevedo, H. ; Arizmendi, C. ; Giraldo, Beatriz F.

Author_Institution

Control & Mecatronica Res. Group, Univ. Autonoma de Bucaramanga, Bucaramanga, Colombia

fYear

2013

fDate

25-28 May 2013

Firstpage

483

Lastpage

486

Abstract

The process of weaning from mechanical ventilation is one of the challenges in intensive care units. 66 patients under extubation process (T-tube test) were studied: 33 patients with successful trials and 33 patients who failed to maintain spontaneous breathing and were reconnected. Each patient was characterized using 7 time series from respiratory signals, and for each serie was evaluated the discrete wavelet transform. It trains a neural network for discriminating between patients from the two groups.

Keywords

discrete wavelet transforms; neural nets; patient treatment; pneumodynamics; time series; ventilation; T-tube test; discrete wavelet transform; extubation process; intensive care units; mechanical ventilation; moment of disconnection; neural network; patients; respiratory signals; spontaneous breathing; time series; weaning; Discrete wavelet transforms; Neural networks; Neurons; Time series analysis; Ventilation; Mechanical Ventilation; Neural Networks; Time series from respiratory signals; Wavelet Transform;

fLanguage

English

Publisher

ieee

Conference_Titel

Complex Medical Engineering (CME), 2013 ICME International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4673-2970-5

Type

conf

DOI

10.1109/ICCME.2013.6548296

Filename

6548296