Key result
The proposed EEMD-based algorithm performed better in removing power line interference from ECG signals and was computationally more efficient than standard EMD and EEMD methods.
The proposed EEMD-based algorithm efficiently removes power line interference from ECG signals, outperforming existing methods in both signal quality and computational speed.
Should not yet change ECG preprocessing practice; hypothesis-generating for refined denoising algorithms.
This study proposes an optimised algorithm to remove power line interference (PLI) from electrocardiogram (ECG) signal based on ensemble empirical mode decomposition (EEMD). A computationally efficient algorithm is one of the important requirements for real‐time monitoring of cardio activities and diagnosis of arrhythmias. Computational complexity in EEMD is significantly reduced by using the EMD as the preprocessing stage. The noisy ECG signal is decomposed into intrinsic mode functions (IMFs) using EMD. ECG signals which are affected by PLI are automatically identified based on the simple ratio of the zero crossing number of IMF components. EEMD is used to decompose only ECG segments constructed from the noisy IMF components. The proposed algorithm is evaluated by real ECG signals available in MIT‐BIH arrhythmia database in terms of signal‐to‐noise ratio and root mean square error. The computational efficiency of this new framework is measured using MATLAB profiling functions and compared with EMD, EEMD, sign‐based adaptive and EMD with wavelet‐based methods. Results show that the proposed algorithm performs better than the EMD, EEMD, sign‐based adaptive and EMD with wavelet‐based methods and it is computationally more efficient than EMD and EEMD methods.
No takes yet. Share an insight, caveat, or question.
Rajeswari Arumugam (2016) studied Arrhythmias (ECG signal processing). Optimised algorithm based on ensemble empirical mode decomposition (EEMD) vs. EMD, EEMD, sign-based adaptive and EMD with wavelet-based methods was evaluated on Signal-to-noise ratio, root mean square error, and computational efficiency. The proposed EEMD-based algorithm performed better in removing power line interference from ECG signals and was computationally more efficient than standard EMD and EEMD methods.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: