Spectral and higher-order statistical analysis of the ECG: Application to the study of ischemia in rabbit isolated hearts

摘要

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.