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IET Wireless Sensor Systems

Micro & Nano Letters

The Journal of Engineering

Review of noise removal techniques in ECG signals

Content Provider	IET Digital Library
Author	Chatterjee, Shubhojeet Thakur, Rini Smita Yadav, Ram Narayan Gupta, Lalita Raghuvanshi, Deepak Kumar
Abstract	An electrocardiogram (ECG) records the electrical signal from the heart to check for different heart conditions, but it is susceptible to noises. ECG signal denoising is a major pre-processing step which attenuates the noises and accentuates the typical waves in ECG signals. Researchers over time have proposed numerous methods to correctly detect morphological anomalies. This study discusses the workflow, and design principles followed by these methods, and classify the state-of-the-art methods into different categories for mutual comparison, and development of modern methods to denoise ECG. The performance of these methods is analysed on some benchmark metrics, viz., root-mean-square error, percentage-root-mean-square difference, and signal-to-noise ratio improvement, thus comparing various ECG denoising techniques on MIT-BIH databases, PTB, QT, and other databases. It is observed that Wavelet-VBE, EMD-MAF, GAN2, GSSSA, new MP-EKF, DLSR, and AKF are most suitable for additive white Gaussian noise removal. For muscle artefacts removal, GAN1, new MP-EKF, DLSR, and AKF perform comparatively well. For base-line wander, and electrode motion artefacts removal, GAN1 is the best denoising option. For power-line interference removal, DLSR and EWT perform well. Finally, FCN-based DAE, DWT (Sym6) soft, MABWT (soft), CPSD sparsity, and UWT are promising ECG denoising methods for composite noise removal.
Starting Page	569
Ending Page	590
Page Count	22
ISSN	17519675
Volume Number	14
e-ISSN	17519683
Issue Number	Issue 9, Dec (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/14/9
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2020.0104
Journal	IET Signal Processing
Publisher Date	2020-07-30
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Additive White Gaussian Noise Removal AKF AWGN Base-line Wander Bioelectric Signal Biology And Medical Computing Biomedical Electrodes Composite Noise Removal CPSD Sparsity Digital Signal Processing DLSR DWT Soft ECG Denoising Method ECG Denoising Technique ECG Signal Denoising Electrical Activity in Neurophysiological Processes Electrical Signal Electrocardiogram Electrocardiography Electrode Motion Artefact Removal Electrodiagnostics And Other Electrical Measurement Technique EMD-MAF FCN-based DAE Function Theory And Analysis GAN1 GAN2 GSSSA Heart Condition Integral Transforms MABWT Medical Disorders Medical Signal Processing MIT-BIH Database MP-EKF Neural Computing Technique Neural Nets Noise Removal Technique Percentage-root-mean-square Difference Power-line Interference Removal Review Reviews And Tutorial Papers Root Mean Square Error Rsource Letters Signal Denoising Signal Processing And Detection Signal-to-noise Ratio Improvement UWT Wavelet Transform Wavelet-VBE
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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