An Efficient Noise Cancellation Technique to Remove Noise from the ECG Signal Using Normalized Signed Regressor LMS Algorithm

Rahman, Mohammad Zia Ur; Ahamed, Shaik Rafi; Reddy, D. V. Rama Koti

doi:10.1109/bibm.2009.39

Cited by 23 publications

(7 citation statements)

References 7 publications

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“…Authors in [8] restructured the electrodes to noncontact, capacitive ECG measurements and both gradiometer designs were compared with standard ECG recording methods and showed detection mismatch employing an open source beat detection algorithm. Authors in [9] proposed the normalized signed regressor LMS (NSRLMS) algorithm to remove ECG noise. Efficient noise reduction, especially of the nonstationary noise was, achieved.…”

Section: Biosignal Acquisition and Processing Techniquesmentioning

confidence: 99%

ECG Noise Reduction with the Use of the Ant Lion Optimizer Algorithm

Hii

Narayanamurthy

Samsuri

2019

Eng. Technol. Appl. Sci. Res.

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The electrocardiogram (ECG) signal is susceptible to noise and artifacts and it is essential to remove that noise in order to support any decision making for automatic heart disorder diagnosis systems. In this paper, the use of Ant Lion Optimizer (ALO) for optimizing and identifying the cutoff frequency of the ECG signal for low-pass filtering is investigated. Generally, the spectrums of the ECG signal are extracted from two classes: arrhythmia and supraventricular. Baseline wander is removed by a moving median filter. A dataset of the extracted features of the ECG spectrums is used to train the ALO. The performance of the ALO is investigated. The ALO-identified cutoff frequency is applied to a Finite Impulse Response (FIR) filter and the resulting signal is evaluated against the original clean and conventional filtered ECG signals. The results show that the intelligent ALO-based system successfully denoised the ECG signals more effectively than the conventional method. The accuracy percentage increased by 2%.

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Section: Biosignal Acquisition and Processing Techniquesmentioning

confidence: 99%

ECG Noise Reduction with the Use of the Ant Lion Optimizer Algorithm

Hii

Narayanamurthy

Samsuri

2019

Eng. Technol. Appl. Sci. Res.

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“…Ambulatory ECG signals/recordings have recently been used for several other purposes like classification of paroxysmal and persistent atrial fibrillation [12], automated recognition of obstructive sleep apnea syndrome [13], an embedded mobile ECG reasoning system for elderly patients [14], ECG signal compression and classification [15], heart rate and accelerometer data fusion for activity assessment [16], a patient adaptive profile scheme for ECG beat classification [17], automatic detection of respiratory rate [18], an intelligent telecardiology system to detect atrial fibrillation [19], etc. In Zia Ur Rehman et al [20], a normalized signal regressor LMS algorithm has been used to cancel the noise from ECG signal.…”

Section: Introductionmentioning

confidence: 99%

RPCA-based detection and quantification of motion artifacts in ECG signals

Kher¹,

Vala²,

Pawar³

et al. 2012

Journal of Medical Engineering & Technology

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In this paper, a recursive principal component analysis (RPCA)-based algorithm is applied for detecting and quantifying the motion artifact episodes encountered in an ECG signal. The motion artifact signal is synthesized by low-pass filtering a random noise signal with different spectral ranges of LPF (low pass filter): 0-5 Hz, 0-10 Hz, 0-15 Hz and 0-20 Hz. Further, the analysis of the algorithm is carried out for different values of SNR levels and forgetting factors (α) of an RPCA algorithm. The algorithm derives an error signal, wherever a motion artifact episode (noise) is present in the entire ECG signal with 100% accuracy. The RPCA error magnitude is almost zero for the clean signal portion and considerably high wherever the motion artifacts (noisy episodes) are encountered in the ECG signals. Further, the general trend of the algorithm is to produce a smaller magnitude of error for higher SNR (i.e. low level of noise) and vice versa. The quantification of the RPCA algorithm has been made by applying it over 25 ECG data-sets of different morphologies and genres with three different values of SNRs for each forgetting factor and for each of four spectral ranges.

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“…Different varieties of adaptive filters have been applied to this problem including least mean squares (LMS) [7]- [9], recursive least squares (RLS), [10], [11], normalized LMS (NLMS) [12], and normalized signed regressor LMS [13]. Despite the popularity of adaptive filters, there is a disadvantage associated with them.…”

Section: Introductionmentioning

confidence: 99%

Epsilon-Tube Filtering: Reduction of High-Amplitude Motion Artifacts From Impedance Plethysmography Signal

Ansari

Ward

Najarian

2015

IEEE J. Biomed. Health Inform.

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The impedance plethysmography (IP) has long been used to monitor respiration. The IP signal is also suitable for portable monitoring of respiration due to its simplicity. However, this signal is very susceptible to motion artifact (MA). As a result, MA reduction is an indispensable part of portable acquisition of the IP signal. Often, the amplitude of the MA is much larger than the amplitude of the respiratory component in the IP signal. This study proposes a novel filtering method to remove the high-amplitude MA's from the IP signal. The proposed method combines the idea of ε-tube loss function and an autoregressive exogenous model to estimate the MA while leaving the periodic respiratory component of the IP signal intact. Also, a regularization method is used to find the best filter coefficients that maximize the regularity of the output signal. The results indicate that the proposed method can effectively remove the MA, outperforming the popular MA reduction methods. Several different performance measures are used for the comparison and the differences are found to be statistically significant.

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An Efficient Noise Cancellation Technique to Remove Noise from the ECG Signal Using Normalized Signed Regressor LMS Algorithm

Cited by 23 publications

References 7 publications

ECG Noise Reduction with the Use of the Ant Lion Optimizer Algorithm

ECG Noise Reduction with the Use of the Ant Lion Optimizer Algorithm

RPCA-based detection and quantification of motion artifacts in ECG signals

Epsilon-Tube Filtering: Reduction of High-Amplitude Motion Artifacts From Impedance Plethysmography Signal

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