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

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Authors

RONZHINA Marina POTOCNAK Tomas JANOUSEK Oto KOLAROVA Jana NOVÁKOVÁ Marie PROVAZNIK Ivo

Year of publication 2012
Type Article in Proceedings
Conference Computing in Cardiology
MU Faculty or unit

Faculty of Medicine

Citation
Web http://cinc.mit.edu/archives/2012/pdf/0645.pdf
Field Physiology
Keywords Rabbits isolated heart; ischemia; ECG classification; cross spectral coherence; higher-order cumulants; neural network
Attached files
Description There are many different approaches for heart beat classification. Probably the main task is extraction of relevant features from the beat. 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%. Thus, they can be successfully used to solve this task.
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