Adaptive thresholding based EMD for delineation of QRS complex in ECG signal analysis

Analyzing the patterns of ECG signals is a vital step in detecting abnormal conditions of the heart. Early detection of cardiac arrhythmia could avoid sudden cardiac death. Artifacts like power line interference and muscle contraction degrades the quality of the recorded ECG signals. In this paper, empirical mode decomposition (EMD) technique used to remove undesirable frequency components in denoising the ECG signals. An adaptive thresholding has been embedded with an EMD algorithm to improve the performance of the proposed method to detect the QRS (Q wave, R wave, S wave) complex. The performance of the proposed method is evaluated in terms of Sensitivity (Se) that results 99.87%, positive predictivity (Pp) of 99.76%, detection error (Er) of 0.41%.The proposed method is found to be more accurate to detect QRS complex in mit-db database compared to cudb database in ECG signal analysis.