A new QRS detector based on empirical mode decomposition

In this paper, a novel QRS detection algorithm based on empirical mode decomposition (EMD) is proposed. The EMD method decomposes the electrocardiogram (ECG) signal into a set of oscillatory components called intrinsic mode functions (IMFs). Calculate the energy ratio between the first IMF (IMF₁) and the ECG signal. If the ratio is more than 5%, the detection layer is reconstructed with the first three IMFs (IMF₁, IMF₂, IMF₃) which are soft-threshold denoised. Else the detection layer will be reconstructed with the second, third and fourth IMF (IMF₂, IMF₃, IMF₄). A simple adaptive threshold is then adopted to detect the QRS complex. And several measures for avoiding false positive detection and false negative detection are taken. The performance of the algorithm has been tested using all 48 records from the MIT-BIH Arrhythmia Database and an average detection rate of 99.62% has been achieved that shows good reliability of the proposed detector.