Detail publikace

ECG classification using neural networks and McSharry model

KIČMEROVÁ, D. PROVAZNÍK, I.

Originální název

ECG classification using neural networks and McSharry model

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

The presented work is focused on modelling of arrhythmias using McSharry model followed by classification using an artificial neural network. The proposed method uses preprocessing of signals with Linear Approximation Distance Thresholding method and Line Segment Clustering method for establishing of initial parameters of McSharry model. The ECG data was taken from standard MIT/BIH arrhythmia database. Multilayer perceptron was used with classification accuracy of 90.1% for distinguishing of premature ventricular contraction and normal beat.

Klíčová slova

ECG, McSharry model, neural networks

Autoři

KIČMEROVÁ, D.; PROVAZNÍK, I.

Rok RIV

2007

Vydáno

22. 8. 2007

Nakladatel

IEEE

Místo

Brno

ISBN

978-80-214-3409-7

Kniha

Proceedings of 5th IEEE Workshop Zvule

Strany od

1

Strany do

1

Strany počet

1

BibTex

@inproceedings{BUT22837,
  author="Dina {Kičmerová} and Valentine {Provazník}",
  title="ECG classification using neural networks and McSharry model",
  booktitle="Proceedings of 5th IEEE Workshop Zvule",
  year="2007",
  pages="1--1",
  publisher="IEEE",
  address="Brno",
  isbn="978-80-214-3409-7"
}