Analysis of cardiorespiratory interaction in patients submitted to the T-tube test in the weaning process implementing symbolic dynamics and neural networks

C. J. Arizmendi, E. H. Solano, H. Gonzalez, H. Gonzalez Acuna, B. F. Giraldo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

The determination of the optimal time of the patients in weaning trial process from Mechanical Ventilation (MV), between patients capable of maintaining spontaneous breathing and patients that fail to maintain spontaneous breathing, is a very important task in intensive care unit. Symbolic Dynamic (SD) and Neural Networks (NN) techniques were applied in order to develop a classifier for the study of patients on weaning trial process. The respiratory pattern of each patient was characterized through different time series. In order to reduce the dimensionality of the system Forward Selection is implemented, obtaining a classification performance result of 85,96 ±6,26% with 64 variables differentiating between 3 classes analyzed at same time.

Original languageEnglish
Title of host publication2018 International Conference on Artificial Intelligence and Big Data, ICAIBD 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages101-105
Number of pages5
ISBN (Electronic)9781538669877
DOIs
StatePublished - 25 Jun 2018
Event2018 International Conference on Artificial Intelligence and Big Data, ICAIBD 2018 - Chengdu, China
Duration: 26 May 201828 May 2018

Publication series

Name2018 International Conference on Artificial Intelligence and Big Data, ICAIBD 2018

Conference

Conference2018 International Conference on Artificial Intelligence and Big Data, ICAIBD 2018
Country/TerritoryChina
CityChengdu
Period26/05/1828/05/18

Keywords

  • Neural networks
  • Signal processing
  • Wean DB
  • Weaning trials

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