Cardiac Arrhythmia Detection based on Signal Variation Characteristic

This paper presents the classification of cardiac arrhythmia based on the signal variation characteristic of each beat type. Considered beat types including the normal beat, fusion beat and premature ventricular contraction beats are differentiated to obtain feature sets. Using the principal component analysis estimation, the detection selects the class by searching the minimal norm of the error vector obtained by basis of each type. Without the help of the timing interval information, the proposed classifier outperforms the algorithm presented in the literature. The classification accuracy of the proposed algorithm achieves perfect detection.