Complexity measure revisited: a new algorithm for classifying cardiac arrhythmias

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.