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Summary: Abstract- This paper deals to the suitability of Complexity
Measure of ECG signals for the classification of cardiac
arrhythmia's. Applying this algorithm to data from the MIT-
BIH database a very poor performance, especially for SR
signals, and an overall error rate of 20% is obtained. In this
study a novel measure, named SPDR, Sample Percentage in the
Dynamic Range, to be used in combination with the
Complexity Measure algorithm, is proposed. Using this novel
proposal the result of the classification is improved decreasing
the overall error rate until to 9%. The algorithm has been
implemented in a computer using LabView and C++ software.
Keywords Biomedical Signal Processing, Arrhythmia
Classification.
I. INTRODUCTION
Reduction of mortality from Ventricular Fibrillation, VF,
Ventricular Tachycardia, VT, and others cardiac causes
depends mainly on rapid detection and accurate
classification of these arrhythmia's. Conventional
algorithms used in both surface ECG monitors and in
implantable cardiovertor/defibrillators rely on simple heart
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