Paper Info
Title
Significance Of Modified Empirical Mode Decomposition For Ecg Denoising
Abstract
The primary objective of the presented work is to exploit the power of modified empirical mode decomposition (M-EMD) for the denoising of ECG signals. It is well known that the ECG signals get corrupted by a number of noises during the recording process. Especially, during wireless ECG recording and ambulatory patient monitoring, the signal gets corrupted by additive white Gaussian noise (AWGN). Over the years, several techniques have been proposed for ECG denoising. Among those, empirical mode decomposition (EMD) and non-local means (NLM) algorithm are noted to be quite effective. Further, the NLM-based approach is better in retaining the morphological characteristics in comparison to the EMD. Consequently, the two approaches are effectively combined in this paper so that each one complements the other. In the proposed approach, the noisy ECG signal is first preprocessed using the NLM algorithm. This is followed by decomposition of the partially denoised output through M-EMD. The decomposed components are suitably thresholded and then reconstructed to obtain the final denoised signal. This largely addresses the issue of under-averaged regions noted in the case of NLM-based denoising. Furthermore, the proposed approach is noted to be superior to the other existing techniques.
Year
DOI
Venue
2017
10.1109/EMBC.2017.8037477
2017 39TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
Keywords
Field
DocType
ECG denoising, NLM, modified EMD, AWGN, thresholding
Noise reduction,Wireless,Pattern recognition,Remote patient monitoring,Computer science,Electronic engineering,Artificial intelligence,Thresholding,Additive white Gaussian noise,Hilbert–Huang transform
Conference
Volume
ISSN
Citations 
2017
1094-687X
0
PageRank 
References 
Authors
0.34
7
3
Name
Order
Citations
PageRank
Pratik Singh141.09
S. Shahnawazuddin26417.34
G. Pradhan38813.14