Feature extraction based on circular summary statistics in ECG signal classification

S.N Torres


In order to explore new patterns for classification
of cardiac signals, taken from the electrocardiogram (ECG), the
circular statistic approach is introduced. Features are extracted
from instantaneous phase of ECG signal using the analytic
signal model based on the Hilbert transform theory. Feature
vectors are used as patterns to distinguish among different
ECG signals. Five types of ECG signals are obtained from
MIT-BIH database. Preliminar results shown that the proposed
features can be used on ECG signal classification problem.

DOI: http://dx.doi.org/http://doi.ieeecomputersociety.org/10.1109/SCCC.2009.24

Categories: Publications