A novel method for R-peak detection in noisy ECG signals using EEMD and ICA

Safari, Amirhossein; Hesar, Hamed Danandeh; Mohebbi, Maryam; Faradji, Farhad

doi:10.1109/icbme.2016.7890948

Cited by 10 publications

(2 citation statements)

References 11 publications

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“…However, if the abdominal signal does not carry these three components, the BSS algorithms fails to separate the FECG from MECG. The ICA based blind source separation [17], was proposed to distinguish FECG from the maternal ECG, however, ICA lacks its ability due to nonstationary nature of FECG and the presence of white noise. The adaptive filtering algorithm has been used for the adaptive noise cancellation from abdominal signal [1].…”

Section: Figurementioning

confidence: 99%

Modified Block Compressed Sensing for Extraction of Fetal Electrocardiogram from Mother Electrocardiogram Using Block Compressed Sensing Based Guided FOCUSS and FAST-Independent Component

Awan

Amir

Maqsood

et al. 2021

ITC

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Fetal ECG extraction from abdominal ECG is critical task for telemonitoring of fetus which require lot of understanding to the subject. Conventional source separation methods are not efficient enough to separate FECG from huge multichannel ECG. Thus use of compression technique is needed to compress and reconstruct ECG signal without any significant losses in quality of signal. Compressed sensing shows promising results for such tasks. However, current compressed sensing theory is not so far that successful due to the non-sparsity and strong noise contamination present in ECG signal. The proposed work explores the concept of block compressed sensing to reconstruct non-sparse FECG signal using GFOCUSS algorithm. The main objective of this paper is not only to successfully reconstruct the ECG signal but to efficiently separate FECG from abdominal ECG. The proposed algorithm is explained in very extensive manner for all experiments. The key feature of proposed method is, that it doesn’t affect the interdependence relation between multichannel ECG. The useof walsh sensing matrix made it possible to achieve high compression ratio. Experimental results shows that even at very high compression ratio, successful FECG reconstruction from raw ECG is possible. These results are validated using PSNR, SINR, and MSE. This shows the framework, compared to other algorithms such as current blocking CS algorithms, rackness CS algorithm and wavelet algorithms, can greatly reduce code execution time during data compression stage and achieve better reconstruction in terms of MSE, PSNR and SINR.

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Section: Figurementioning

confidence: 99%

Modified Block Compressed Sensing for Extraction of Fetal Electrocardiogram from Mother Electrocardiogram Using Block Compressed Sensing Based Guided FOCUSS and FAST-Independent Component

Awan

Amir

Maqsood

et al. 2021

ITC

View full text Add to dashboard Cite

show abstract

“…Thus, analyzing the proposed method effectiveness of the proposed method improved the SNR, MSE rate better when compared with the denoising algorithm as per the previous denoising techniques used. The proposed technique will solve the shortcoming of the first order IMF disorder better when compared with the traditional EMD denoising technique improves in terms of hard threshold function and traditional soft function [9,10] Thus, to overcome the problems that occurred in the existing approaches to perform denoising, a hybrid transform model combined Multiscale local polynomial technique (MLPT) and EEMD is model. The developed model discarded the first-order IMF in the conventional EMD denoising approach and a new threshold denoising function was developed.…”

Section: Introductionmentioning

confidence: 99%

An ECG Denoising Method Based on Hybrid MLTP-EEMD Model

2022

IJIES

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The Electrocardiogram signal (ECG) is highly susceptible to the electrical environment from where the motion artifacts were being recorded. The accurate representation of the ECG signal will necessitate removing the noise from various sources thereby resulting in a noise-free model. This present research work uses Multi scale Local Polynomial Transform (MLPT) technique that provides wavelet transform as an alternative when the MLPT model was non-equispaced. The proposed research combines two approaches such as MLPT and Ensemble Empirical Mode Decomposition (EEMD) forming a Hybrid Transform Model which is used for denoising in the research. The present research work considers white Gaussian noise and experimental results are based on the MIT-BIH Physionet Database. The results of the proposed hybrid MLPT-EEMD obtained better SNR values of 25.93 dB when compared to the existing Empirical Mode Decomposition technique (EMD) of 5.43dB, EMD with adaptive switching mean filter obtained 9.135 dB and S-Transform based Time-Frequency Filtering Approach obtained 13.82 dB.

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Development of robust, fast and efficient QRS complex detector: a methodological review

Raj

Ray

Shankar

2018

Australas Phys Eng Sci Med

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The basis and reliability for timely diagnosis of cardiovascular diseases depend on the robust and accurate detection of QRS complexes along with the fiducial points in the electrocardiogram (ECG) signal. Despite, the several QRS detection algorithms reported in the literature, the development of an efficient QRS detector remains a challenge in the clinical environment. Therefore, this article summarizes the performance analysis of various QRS detection techniques depending upon three assessment factors which include robustness to noise, computational load, and sensitivity validated on the benchmark MIT-BIH arrhythmia database. Moreover, the limitations of these algorithms are discussed and compared with the standard signal processing algorithms, followed by the future suggestions to develop a reliable and efficient QRS methodology. Further, the suggested method can be implemented on suitable hardware platforms to develop smart health monitoring systems for continuous and long-term ECG assessment for real-time applications.

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A novel method for R-peak detection in noisy ECG signals using EEMD and ICA

Cited by 10 publications

References 11 publications

Modified Block Compressed Sensing for Extraction of Fetal Electrocardiogram from Mother Electrocardiogram Using Block Compressed Sensing Based Guided FOCUSS and FAST-Independent Component

Modified Block Compressed Sensing for Extraction of Fetal Electrocardiogram from Mother Electrocardiogram Using Block Compressed Sensing Based Guided FOCUSS and FAST-Independent Component

An ECG Denoising Method Based on Hybrid MLTP-EEMD Model

Development of robust, fast and efficient QRS complex detector: a methodological review

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