Empirical mode decomposition based filtering techniques for power line interference reduction in electrocardiogram using various adaptive structures and subtraction methods

Suchetha, M.; Kumaravel, N.

doi:10.1016/j.bspc.2013.05.001

Cited by 63 publications

(27 citation statements)

References 22 publications

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“…8 In Ref. [9] four techniques for the cancellation of ECG noise were proposed using an EMD based on two adaptive filter structure weights. A simple technique for the ECG signals artifacts cancellation using normalized adaptive filters has been proposed as an application of wireless biotelemetry.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Filtering Approach for Denoising Electrocardiogram Signal Using Moving Average Filter

Salih¹,

Aljunid²,

Aljunid³

et al. 2015

J Med Imaging Hlth Inform

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The noise within an electrocardiogram signal can cause errors that are viewed in the results of different ECG characteristics, in both amplitude and time interval which ultimately lead to a incorrect diagnosis of cardiac disease. In this paper, a new approach of de-noising the electrocardiogram signal is proposed using multiiteration of the moving average filter. The algorithm of the proposed approach includes two main steps: first to estimate the amount of noise presents in the ECG signal, second to remove the noise added. The proposed de-noising approach is validated with ECG records which were collected from the MIT-BIH ECG database with different amounts of additive gauss white noise. The validation results prove the robustness of proposed denoising approach to provide the greatest signal to noise ratio improvement, and to give a reduction of 50% or more in terms of standard metrics used for computing distortion in a noisy signal. Additionally, the filtered signal has a smooth shape in comparison with the adopted de-noising ECG signal techniques.

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Section: Introductionmentioning

confidence: 99%

Adaptive Filtering Approach for Denoising Electrocardiogram Signal Using Moving Average Filter

Salih¹,

Aljunid²,

Aljunid³

et al. 2015

J Med Imaging Hlth Inform

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“…EMG is often eliminated as high-frequency noise. Empirical mode decomposition (EMD) [2,3] decomposes the signal into a sum of intrinsic mode functions (IMFs) arranged in order of frequency and then eliminates EMG adaptively. However, the drawback of this method is that the end effects must be restrained effectively to achieve better performance.…”

Section: Introductionmentioning

confidence: 99%

A new modified wavelet-based ECG denoising

Wang

Zhu

Yan

2019

Computer Assisted Surgery

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Purpose: Wavelet denoising is one of the denoising methods commonly used for ECG signals. However, due to the frequency overlap between the EMG and ECG, the feeble characteristics of ECG signals exists the risk of being weakened in the process of filtering noise. This paper presents a method of modified wavelet design and applies it to the denoising of ECG signals. Materials and methods: The optimized filter coefficients are obtained by approximating the amplitude-frequency response of the ideal filter, and the wavelet is constructed with the optimized filter coefficients. The algorithm is tested by clinical ECG data. Results: The results show that the proposed denoising method can remove the high-frequency noise effectively and enhance the characteristic information of P waves and T waves, and retain the characteristic information of the atrial fibrillation signals simultaneously. Compared with db4 and sym4 wavelets, the proposed wavelet can improve the signal to noise ratio and reduce the mean square error effectively at the same time. Conclusion: The modified wavelet design method proposed in this paper can effectively remove high-frequency noise while retaining and enhancing weak features. It provides a theoretical guidance for the de-noising of ECG signals in mobile medicine and also provides a way for other types of weak feature signal denoising.

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“…This algorithm overcomes the limitation in conventional method of ECG noise reduction in preserving all characteristics of QRS complex in the presence of noise; also the finding results of signal to noise ratio (SNR) are perfect in comparison to some existing methods. In [10], another EMD based approach was proposed to eliminate the power line interference in ECG signals. An efficient and simple technique for cancellation of artifacts in ECG signals using normalized adaptive filters was presented in [11] as an application of wireless biotelemetry.…”

Section: Introductionmentioning

confidence: 99%

“…Original ECG signal record 100 from MIT-BIH DB. In left side, the signal is corrupted with different noise levels(5,10,15, 20, and 25 dB) and right side contains the clean signal obtained by proposed approach…”

mentioning

confidence: 99%

Robust Approach of De-noising ECG Signal Using Multi-Resolution Wavelet Transform

Jaenul¹,

Al-Yousif²,

Alrawi³

et al. 2018

IJET

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The ECG signal expresses the behavior of human heart against time. The analysis of this signal performs great information for diagnosing different cardiac diseases. In other hand, the ECG signal used for analyzing must be clean from any type of noises that corrupted it by the external environment. In this paper, a new approach of ECG signal noise reduction is proposed to minimize noise from all parts of ECG signal and maintains main characteristics of ECG signal with lowest changes. The new approach applies simple scaling down operation on the detail resolution in the wavelet transform space of noisy signal. The proposed noise reduction approach is validated by some ECG records from MIT-BIH database. Also, the performance of the proposed approach is evaluated graphically using different SNR levels and some standard metrics. The results improve the ability of the proposed approach to reduce noise from the ECG signal with high accuracy in comparison to the existing methods of noise reduction.

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Empirical mode decomposition based filtering techniques for power line interference reduction in electrocardiogram using various adaptive structures and subtraction methods

Cited by 63 publications

References 22 publications

Adaptive Filtering Approach for Denoising Electrocardiogram Signal Using Moving Average Filter

Adaptive Filtering Approach for Denoising Electrocardiogram Signal Using Moving Average Filter

A new modified wavelet-based ECG denoising

Robust Approach of De-noising ECG Signal Using Multi-Resolution Wavelet Transform

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