Detail publikace

Heart beats classification using artificial neural network

SMÍŠEK, R. RONZHINA, M.

Originální název

Heart beats classification using artificial neural network

Český název

Heart beats classification using artificial neural network

Anglický název

Heart beats classification using artificial neural network

Typ

článek ve sborníku

Jazyk

cs

Originální abstrakt

Use of artificial neural network (ANN) for automatic clasification of the heart beats is highly topical. Both appropriate preparation of ECG data as well as selection of the ANN model allow performing effective and correct classification. The type of segments selected from ECG influences not only the type and maximum number of recognized classification groups but also the complexity of classification model. The latter affects PC memory requirements as well as the time needed for the classification. The main goals of this work are to design ANN model for heart beats classification and to study the influence of various factors (such as character of ECG data, ANN topology, etc.) on the results of classification.

Český abstrakt

Use of artificial neural network (ANN) for automatic clasification of the heart beats is highly topical. Both appropriate preparation of ECG data as well as selection of the ANN model allow performing effective and correct classification. The type of segments selected from ECG influences not only the type and maximum number of recognized classification groups but also the complexity of classification model. The latter affects PC memory requirements as well as the time needed for the classification. The main goals of this work are to design ANN model for heart beats classification and to study the influence of various factors (such as character of ECG data, ANN topology, etc.) on the results of classification.

Anglický abstrakt

Use of artificial neural network (ANN) for automatic clasification of the heart beats is highly topical. Both appropriate preparation of ECG data as well as selection of the ANN model allow performing effective and correct classification. The type of segments selected from ECG influences not only the type and maximum number of recognized classification groups but also the complexity of classification model. The latter affects PC memory requirements as well as the time needed for the classification. The main goals of this work are to design ANN model for heart beats classification and to study the influence of various factors (such as character of ECG data, ANN topology, etc.) on the results of classification.

Klíčová slova

Electrocardiogram, heart beat classification, artificial neural network, isolated heart

Rok RIV

2013

Vydáno

25.04.2013

ISBN

978-80-214-4695-3

Kniha

Proceedings of the 19th Conference Student EEICT 2013

Strany od

166

Strany do

168

Strany počet

3

BibTex


@inproceedings{BUT99448,
  author="Radovan {Smíšek} and Marina {Ronzhina}",
  title="Heart beats classification using artificial neural network",
  annote="Use of artificial neural network (ANN) for automatic clasification of the heart beats is highly topical. Both appropriate preparation of ECG data as well as selection of the ANN model allow performing effective and correct classification. The type of segments selected from ECG influences not only the type and maximum number of recognized classification groups but also the complexity of classification model. The latter affects PC memory requirements as well as the time needed for the classification. The main goals of this work are to design ANN model for heart beats classification and to study the influence of various factors (such as character of ECG data, ANN topology, etc.) on the results of classification.",
  booktitle="Proceedings of the 19th Conference Student EEICT 2013",
  chapter="99448",
  howpublished="print",
  year="2013",
  month="april",
  pages="166--168",
  type="conference paper"
}