Técnicas estadísticas para diagnóstico de arritmias ventriculares
- Cabello Ferrer, Diego
- Salceda, J.M.
- Barro, Senén
- Ruiz, R.
- Mira Mira, José
ISSN: 0210-8712
Year of publication: 1989
Year: 22
Issue: 4
Pages: 45-52
Type: Article
More publications in: Revista de informática y automática
Abstract
We have faced the detection of life threatening ventricular arrythmias applaing statistical techniques on a training set of 90 ECG registers. After the phase of properties extracting each one of these registers is characterized by a vector composed of 7 spectral characteristics. Because we work on a small sets of samples, they are not representatives of the probability distributions, and because the fact that we work with imprecisely defined categories, we have considered fuzzy clasificators which are based on K-NN rules in order to obtain betterresults. Labels adscriptionon the training set is carried out using fuzzy clustering algorithm (fuzzy C-means and fuzzy covariance algorithms). The fuzzy covariance algorithm shows clusters associated to categories of ECG registers. This information is the base for a K-NN fuzzy clasificator which detects new cases of ventricular arrhythmias with a high degree of reliability.