Data-Driven Computer-Aided Diagnosis of Ventricular Fibrillation Based on Ensemble Empirical Mode Decomposition of ECG

Seung-Rok Oh, Young-Seok Choi

http://doi.org/10.5626/JOK.2020.47.4.387

In this paper, we propose a novel computer-aided diagnosis method to detect VF(ventricular fibrillation), one of the hazardous cardiac symptoms of arrhythmia by applying the EEMD(Ensemble Empirical Mode Decomposition) to the ECG signals. Using the EEMD to the ECG signals, it is shown that VF in the EMD region has a higher correlation with the IMFs (intrinsic mode functions) than the NSR (normal sinus rhythm) and other types of arrhythmia. To quantify this characteristic, we calculate the angle between the ECG signal and the specific IMFs, and classify the pathology by differentiating the angles. To verify the effectiveness of the proposed algorithm, we measured the accuracy of diagnosis using arrhythmia data from the PhysioNet database and confirm capacity of the proposed method.