Detail publikace

Spectral and Higher-Order Statistics Analysis of ECG: Application to Study of Ischemia in Rabbit Isolated Hearts

Originální název

Spectral and Higher-Order Statistics Analysis of ECG: Application to Study of Ischemia in Rabbit Isolated Hearts

Anglický název

Spectral and Higher-Order Statistics Analysis of ECG: Application to Study of Ischemia in Rabbit Isolated Hearts

Jazyk

en

Originální abstrakt

The present paper is focused on the study of ECG cross spectral coherence and higher-order cumulants and their ability to classify normal and ischemic cardiac beats. Using these parameters as the input for neural network classifier allows achieving classification error only 4%.

Anglický abstrakt

The present paper is focused on the study of ECG cross spectral coherence and higher-order cumulants and their ability to classify normal and ischemic cardiac beats. Using these parameters as the input for neural network classifier allows achieving classification error only 4%.

BibTex


@inproceedings{BUT93840,
  author="Marina {Ronzhina} and Tomáš {Potočňák} and Oto {Janoušek} and Jana {Kolářová} and Marie {Nováková} and Ivo {Provazník}",
  title="Spectral and Higher-Order Statistics Analysis of ECG: Application to Study of Ischemia in Rabbit Isolated Hearts",
  annote="The present paper is focused on the study of ECG cross spectral coherence and higher-order cumulants and their ability to classify normal and ischemic cardiac beats. Using these parameters as the input for neural network classifier allows achieving classification error only 4%.",
  booktitle="Computing in Cardiology 2012",
  chapter="93840",
  howpublished="electronic, physical medium",
  year="2012",
  month="september",
  pages="645--648",
  type="conference paper"
}