Resumen
The estimate of the optimal time to remove the ventilator from a patient in intensive care remains critical in clinical practice. This study analyzes the breathing pattern from cardiorespiratory signals extubation patients undergoing performing resampling the signal, then the Symbolic Dynamics technique for data processing is implemented, together with the techniques of Support Vector Machines (SVM) and Linear Discriminant Analysis (LDA) for classifying 154 patients conglomerates in the Group Success and Failure Group classification, obtaining the best result obtained from 93.87 ± 0.01 % prediction, for SVM.
Idioma original | Inglés |
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Páginas (desde-hasta) | 465-468 |
Número de páginas | 4 |
Publicación | IFMBE Proceedings |
DOI | |
Estado | Publicada - 2017 |
Evento | 7th Latin American Congress on Biomedical Engineering, CLAIB 2016 - Bucaramanga, Santander, Colombia Duración: 26 oct. 2016 → 28 oct. 2016 |
Líneas de Investigación UNAB
- Automatización y Control