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Journal articles on the topic 'ECG signal interference'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Smolarik, Lukas, Dusan Mudroncik, and Lubos Ondriga. "ECG Signal Processing." Advanced Materials Research 749 (August 2013): 394–400. http://dx.doi.org/10.4028/www.scientific.net/amr.749.394.

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Electrocardiography (ECG) is a diagnostic method that allows sensing and record the electric activity of heart [. The measurement of electrical activity is used as a standard twelve-point system. At each of these leads to measure the useful signal and interference was measured. The intensity of interference depends on the artefacts (electrical lines, brum, motion artefacts, muscle, interference from the environment, etc.). For correct evaluation of measured signal there is a need to processing the measured signal to suitable form. At present, the use of electrocardiograms with sensors with con

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Mohan, Neethu, Sachin Kumar S, Prabaharan Poornachandran, and Soman K.P. "Modified Variational Mode Decomposition for Power Line Interference Removal in ECG Signals." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 1 (2016): 151. http://dx.doi.org/10.11591/ijece.v6i1.8592.

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Power line interferences (PLI) occurring at 50/60 Hz can corrupt the biomedical recordings like ECG signals and which leads to an improper diagnosis of disease conditions. Proper interference cancellation techniques are therefore required for the removal of these power line disturbances from biomedical recordings. The non-linear time varying characteristics of biomedical signals make the<strong> </strong>interference removal a difficult task without compromising the actual signal characteristics. In this paper, a modified variational mode decomposition based approach is proposed fo

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Mohan, Neethu, Sachin Kumar S, Prabaharan Poornachandran, and Soman K.P. "Modified Variational Mode Decomposition for Power Line Interference Removal in ECG Signals." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 1 (2016): 151. http://dx.doi.org/10.11591/ijece.v6i1.pp151-159.

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Power line interferences (PLI) occurring at 50/60 Hz can corrupt the biomedical recordings like ECG signals and which leads to an improper diagnosis of disease conditions. Proper interference cancellation techniques are therefore required for the removal of these power line disturbances from biomedical recordings. The non-linear time varying characteristics of biomedical signals make the<strong> </strong>interference removal a difficult task without compromising the actual signal characteristics. In this paper, a modified variational mode decomposition based approach is proposed fo

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Kumar, M. Suresh, G. Krishnamoorthy, and D. Vaithiyanathan. "Synchrosqueezing Transform Based Powerline Interference Reduction in ECG Recording." Journal of Medical Imaging and Health Informatics 10, no. 10 (2020): 2259–73. http://dx.doi.org/10.1166/jmihi.2020.3174.

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This paper presents an adaptive ECG enhancement procedure based on Synchrosqueezing Transform (SST) to eliminate Powerline interference (PLI) from ECG signal. This work also incorporates the principles of modified discrete cosine transform (MDCT) and wiener filter. PLI is a major source of artifacts in the ECG signal which can affect its interpretation. Separating PLI from ECG signal poses a great challenge in the ECG analysis. The existing PLI removal techniques suffer from two major drawbacks such as Mode Mixing, inability to deal with non-stationary characteristics of signal. In this paper,

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Peng, Yan, and Zhi Gang Qin. "The Design of a Filter System for ECG Signal." Applied Mechanics and Materials 513-517 (February 2014): 3757–60. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.3757.

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According to the process of the ECG signal extraction, the ECG signal is susceptible to interference which will affect the quality and effect of ECG test. In this essay, we designed an ECG signal filtering system based on ARM. It can filter the interference signal and reduce the interference of the common mode signal and power frequency, through the design circuit of the preamplifier, post amplification, filtering, notch filtering, and power amplification. Thus, ECG signal will be better collected and met the best demand.

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Ma, Jing, Jun Xu, Hai Bo Xu, Yu Wang, and Sheng Xu Yin. "Design of ECG Signal Acquisition and Processing Circult." Applied Mechanics and Materials 236-237 (November 2012): 856–61. http://dx.doi.org/10.4028/www.scientific.net/amm.236-237.856.

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ECG signal is, as a vital method performed on the heart study and clinical diagnosis of cardiovascular diseases, an important human physiological signal, containing the human cardiac conduction system of physiological and pathological information. Aiming at the weak low frequency characteristic of ECG signals, the core circuit based on the AD620 and LM324 amplifier is given. After analyzing the major components of the ECG signal and the frequency range of interference, weak ECG signal collected by the electrodes is amplified by the preamplifier circuit, and the interference then is wiped out b

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Huang, Jian-Jia, Chung-Yu Chang, Jen-Kuang Lee, and Hen-Wai Tsao. "RESOLVING SINGLE-LEAD ECG FROM EMG INTERFERENCE IN HOLTER RECORDING BASED ON EEMD." Biomedical Engineering: Applications, Basis and Communications 26, no. 01 (2014): 1450008. http://dx.doi.org/10.4015/s1016237214500082.

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The aim of this study was to propose an electrocardiogram (ECG) de-noising framework based on ensemble empirical mode decomposition (EEMD) to eliminate electromyography (EMG) interference without signal distortion. ECG signals are easily corrupted by EMG, especially in Holter monitor recordings. The frequency component overlapping between EMG and ECG is a challenge in signal processing that remains to be solved. The aim of the present study, therefore, was to resolve ECG signals from recorded segments with EMG noise. Two units were put into our proposed framework; first, modified moving averag

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Ladrova, Martina, Radek Martinek, and René Jaros. "Power Line Interference Elimination in ECG Signals." Journal of Biomimetics, Biomaterials and Biomedical Engineering 41 (April 2019): 105–15. http://dx.doi.org/10.4028/www.scientific.net/jbbbe.41.105.

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The recordings of electrocardiogram (ECG), as an important biological signal which provides a valuable basis for the clinical diagnosis and treatment, are often corrupted by the wide range of artifacts. One important of them is power line interference (PLI). The overlapping interference affects the quality of ECG waveform, leading to the false detection and recognition of wave groups, and thus causing faulty treatment or diagnosis. The study deals with some of the signal processing approaches frequently used for elimination of PLI in ECG signal and compares the accuracy of methods by evaluatio

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Jagannaveen, V., K. Murali Krishna, and K. Raja Rajeswari. "Noise reduction in ECG signals for bio-telemetry." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 2 (2019): 1028. http://dx.doi.org/10.11591/ijece.v9i2.pp1028-1035.

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<p>In Biotelemetry, Biomedical signal such as ECG is extremely important in the diagnosis of patients in remote location and is recorded commonly with noise. Considered attention is required for analysis of ECG signal to find the patho-physiology and status of patient. In this paper, LMS and RLS algorithm are implemented on adaptive FIR filter for reducing power line interference (50Hz) and (AWGN) noise on ECG signals .The ECG signals are randomly chosen from MIT_BIH data base and de-noising using algorithms. The peaks and heart rate of the ECG signal are estimated. The measurements are

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Venkat, Neeraj. "Representation and Denoising of ECG Signal Using Hybrid Filtering Approach." International Journal for Research in Applied Science and Engineering Technology 9, no. VII (2021): 3281–86. http://dx.doi.org/10.22214/ijraset.2021.37044.

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Electrocardiogram (ECG) signal plays an imperative role in monitoring and examining the health condition of the heart. ECG signal represents the electrical activity of the heat. The most consequential noises that degrade important features in ECG signal are powerline interference noise, external electromagnetic field interference noise, baseline wandering and electroencephalogram noise. The features of ECG signal obtained in time domain is not sufficient for analyzing the ECG signal. As the signal is non-stationary, the time-frequency representation can be used for feature extraction. The Shor

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Naveen, V. Jagan, K. Murali Krishna, and K. Raja Rajeswari. "Noise reduction in ECG Signals for Bio-telemetryb." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 1 (2019): 505. http://dx.doi.org/10.11591/ijece.v9i1.pp505-511.

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<p><span lang="EN-US">In Biotelemetry, Biomedical signal such as ECG is extremely important in the diagnosis of patients in remote location and is recorded commonly with noise. Considered attention is required for analysis of ECG signal to find the patho-physiology and status of patient. In this paper, LMS and RLS algorithm are implemented on adaptive FIR filter for reducing power line interference (50Hz) and (AWGN) noise on ECG signals .The ECG signals are randomly chosen from MIT_BIH data base and de-noising using algorithms. The peaks and heart rate of the ECG signal are estimat

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Lakshmi, P. Sri, and V. Lokesh Raju. "ECG De-noising using Hybrid Linearization Method." TELKOMNIKA Indonesian Journal of Electrical Engineering 15, no. 3 (2015): 504. http://dx.doi.org/10.11591/tijee.v15i3.1568.

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<p>Electrocardiogram (ECG) is a non-invasive tool that monitors the electrical activity of the heart. An ECG signal is highly prone to the disturbances such as noise contamination, artifacts and other signals interference. So, an ECG signal has to be de-noised so that the distortions can be eliminated from the original signal for the perfect diagnosing of the condition and performance of the heart. Extended Kalman Filter (EKF) de-noises an ECG signal to some extent. This project proposes a method called Hybrid Linearization Method which is a combination of Extended Kalman Filter along wi

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13

Xiong, Hui, Chunhou Zheng, Jinzhen Liu, and Limei Song. "ECG Signal In-Band Noise De-Noising Base on EMD." Journal of Circuits, Systems and Computers 28, no. 01 (2018): 1950017. http://dx.doi.org/10.1142/s0218126619500178.

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The electrocardiogram (ECG) signal is widely used for diagnosis of heart disorders. However, ECG signal is a kind of weak signal to be interfered with heavy background interferences. Moreover, there are some overlaps between the interference frequency sub-bands and the ECG frequency sub-bands, so it is difficult to inhibit noise in the ECG signal. In this paper, the ECG signal in-band noise de-noising method based on empirical mode decomposition (EMD) is proposed. This method uses random permutation to process intrinsic mode functions (IMFs). It abstracts QRS complexes to separate them from no

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Zhang, Qifei, Lingjian Fu, and Linyue Gu. "A Cascaded Convolutional Neural Network for Assessing Signal Quality of Dynamic ECG." Computational and Mathematical Methods in Medicine 2019 (October 20, 2019): 1–12. http://dx.doi.org/10.1155/2019/7095137.

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Motion artifacts and myoelectrical noise are common issues complicating the collection and processing of dynamic electrocardiogram (ECG) signals. Recent signal quality studies have utilized a binary classification metric in which ECG samples are determined to either be clean or noisy. However, the clinical use of dynamic ECGs requires specific noise level classification for varying applications. Conventional signal processing methods, including waveform discrimination, are limited in their ability to remove motion artifacts and myoelectrical noise from dynamic ECGs. As such, a novel cascaded c

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Fu, Xiu Hui, Hong Ru Lin, Shu Li Ouyang, and Wei Bo Song. "Design of Portable ECG Tester." Advanced Materials Research 328-330 (September 2011): 228–31. http://dx.doi.org/10.4028/www.scientific.net/amr.328-330.228.

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In order to solve the problem of ECG acquisition and processing better, this paper designs a portable ECG tester, which uses the SCM as the core controller. Power basic frequency interference was removed by 50 Hz trap filter. Power harmonic interference, electrode polarization interference and my electricity interference were removed by low- pass filter. Baseline drift was removed by high- pass filter. At the same time; we test the performance of acquisition circuit, filter circuit and amplification circuit. As a result, it is shown that the system can well collect and process ECG signal.

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Chhavi Saxena, Dr, Dr Avinash Sharma, Dr Rahul Srivastav, and Dr Hemant Kumar Gupta. "Denoising of Ecg Signals Using Fir & Iir Filter: a Performance Analysis." International Journal of Engineering & Technology 7, no. 4.12 (2018): 1. http://dx.doi.org/10.14419/ijet.v7i4.12.20982.

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Electrocardiogram (ECG) signal is the electrical recording of coronary heart activity. It is a common routine and vital cardiac diagnostic tool in which in electric signals are measured and recorded to recognize the practical status of heart, but ECG signal can be distorted with noise as, numerous artifacts corrupt the unique ECG signal and decreases it quality. Consequently, there may be a need to eliminate such artifacts from the authentic signal and enhance its quality for better interpretation. ECG signals are very low frequency signals of approximately 0.5Hz-100Hz and digital filters are

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Zhang, Ai Hua, Ming Chun Kou, Chen Diao, and Dong Mei Lin. "Quality Assessment of ECG Signal Based on Wavelet Energy Ratio and Wavelet Energy Entropy." Applied Mechanics and Materials 530-531 (February 2014): 577–80. http://dx.doi.org/10.4028/www.scientific.net/amm.530-531.577.

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ECG signal is affected by many factors such as noise and interference in the process of acquisition, which make it difficult for clinicians to interpret the ECG signal precisely and effectively. In order to detect whether an ECG signal is worthy to be interpreted by clinicians, an algorithm was proposed to assess the quality of ECG signal based on wavelet energy ratio and wavelet energy entropy. After wavelet decomposition, the ECG signals wavelet energy ratio and wavelet energy entropy were calculated in three different frequency bands, and we defined them as the quality indices to evaluate t

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Zhao, Huayu. "Design and Application of Human Movement Respiratory and ECG Signal Acquisition System." Journal of Medical Imaging and Health Informatics 10, no. 4 (2020): 890–97. http://dx.doi.org/10.1166/jmihi.2020.2950.

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To realize the design of mobile phone human movement breathing and electrocardiograph (ECG) signal acquisition system based on Bluetooth transmission, the principle of the generation and detection of ECG and respiratory signal and the guide system of signal acquisition are analyzed. Additionally, the hardware of the system is designed, including the hardware of the signal acquisition system, the design of ADS1292R ECG and respiratory signal acquisition module, the design of the main control chip and the design of the Bluetooth module. Then, the digital filtering processing of the ECG and respi

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D’Aloia, Matteo, Annalisa Longo, and Maria Rizzi. "Noisy ECG Signal Analysis for Automatic Peak Detection." Information 10, no. 2 (2019): 35. http://dx.doi.org/10.3390/info10020035.

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Cardiac signal processing is usually a computationally demanding task as signals are heavily contaminated by noise and other artifacts. In this paper, an effective approach for peak point detection and localization in noisy electrocardiogram (ECG) signals is presented. Six stages characterize the implemented method, which adopts the Hilbert transform and a thresholding technique for the detection of zones inside the ECG signal which could contain a peak. Subsequently, the identified zones are analyzed using the wavelet transform for R point detection and localization. The conceived signal proc

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Li, Xu Wen, Bi Wei Zhang, and Qiang Wu. "Study for Detection Algorithm of QRS Complex in ECG Signal." Advanced Materials Research 765-767 (September 2013): 2105–8. http://dx.doi.org/10.4028/www.scientific.net/amr.765-767.2105.

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In ECG signals accurate detection to the position of QRS complex is a key to automatic analysis and diagnosis system. And its premise is that effectively remove all kinds of noise interference in ECG signal. Here, a method of detecting QRS based on EMD and wavelet transform was presented which is aim to improve the anti-noise performance of the detection algorithm. It is combined EMD with the theory of singularity detecting based on wavelet transform modulus maxima method. It has the high detection accuracy and good precision that can give an effective way to the automatic analysis for ECG sig

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Wang, Bao Jie, Yan Men, and Gang Zheng. "A Frequency Tracking Adaptive Power Line Interference Canceller for Electrocardiogram." Applied Mechanics and Materials 556-562 (May 2014): 1506–9. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.1506.

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Power line interference (PLI) may lead to the signal-to-noise ratio (SNR) decline sharply on biomedical signals, including the electrocardiogram (ECG). The proposed method employs the relationship of frequency and weights in adaptive filter to track the frequency variation of PLI. Real ECG signals from MIT-BIH database was used in the experiment, and they were corrupt by an artificial PLI signal for experiment. Correction performances of the proposed method and traditional adaptive method were compared by SNR in the paper. The results showed that the proposed method is consistently superior to

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Heriana, Octa, and Ali Matooq Al Misbah. "Comparison of Wavelet Family Performances in ECG Signal Denoising." Jurnal Elektronika dan Telekomunikasi 17, no. 1 (2017): 1. http://dx.doi.org/10.14203/jet.v17.1-6.

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The heart is considered the most important organ of our body that controls the circulation of blood throughout the body. Measured heartbeat signals can be further analyzed in order to know the health condition of a person. The challenge of ECG signal measurement and analysis is how to remove the noises imposed on the signal that is interfered from many different sources, such as internal noise in sensor devices, power line interference, muscle activity, and body movements. This paper implemented wavelet transform to reduce the noise imposed on the ECG signal to get a closely actual heart signa

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Viswanadham, Talabattula, and Rajesh Kumar P. "Artefacts Removal from ECG Signal: Dragonfly Optimization-based Learning Algorithm for Neural Network-enhanced Adaptive Filtering." Scalable Computing: Practice and Experience 21, no. 2 (2020): 247–63. http://dx.doi.org/10.12694/scpe.v21i2.1657.

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Electrocardiogram (ECG) artefact removal is the major research topic as the pure ECG signals are an essential part of diagnosing heart-related problems. ECG signals are highly prominent to the interaction with the other signals like the Electromyography (EMG), Electroencephalography (EEG), and Electrooculography (EOG) signals and the interference mainly occurs at the time of recording. The removal of the artefacts from the ECG signal is a hectic challenge, for which, a novel algorithm is proposed in this work. The proposed method utilizes the adaptive filter termed as the (Dragonfly optimizati

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Bhateja, Vikrant, Rishendra Verma, Rini Mehrotra, and Shabana Urooj. "A Non-Linear Approach to ECG Signal Processing using Morphological Filters." International Journal of Measurement Technologies and Instrumentation Engineering 3, no. 3 (2013): 46–59. http://dx.doi.org/10.4018/ijmtie.2013070104.

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Analysis of the Electrocardiogram (ECG) signals is the pre-requisite for the clinical diagnosis of cardiovascular diseases. ECG signal is degraded by artifacts such as baseline drift and noises which appear during the acquisition phase. The effect of impulse and Gaussian noises is randomly distributed whereas baseline drift generally affects the baseline of the ECG signal; these artifacts induce interference in the diagnosis of cardio diseases. The influence of these artifacts on the ECG signals needs to be removed by suitable ECG signal processing scheme. This paper proposes combination of no

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Li, Guo Jun, Xiao Jie Hao, Hui Zhong, and Xiao Na Zhou. "Separating Nonstationary Powerline Interference from ECG Using Empirical Mode Decomposition." Applied Mechanics and Materials 155-156 (February 2012): 736–40. http://dx.doi.org/10.4028/www.scientific.net/amm.155-156.736.

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Powerline interference (PLI) is a significant source of noise in Electrocardiogram (ECG). It often exhibits variations in frequency and amplitude along with relatively lower level than that of ECG signal in battery-operated ECG system, whose separation remains a challenging task. The use of masking signal-aided empirical mode decomposition is presented to deal with this problem in this study. Simulation results show that our method can effectively decompose the time-varying PLI into a single intrinsic mode function (IMF) at various interference levels.

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Lin, Yue-Der, and Yu Hen Hu. "Power-Line Interference Detection and Suppression in ECG Signal Processing." IEEE Transactions on Biomedical Engineering 55, no. 1 (2008): 354–57. http://dx.doi.org/10.1109/tbme.2007.902234.

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Oo, Thandar, and Pornchai Phukpattaranont. "Accounting for SNR in an Algorithm Using Wavelet Transform to Remove ECG Interference from EMG Signals." Fluctuation and Noise Letters 19, no. 01 (2019): 2050001. http://dx.doi.org/10.1142/s0219477520500017.

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When the electromyography (EMG) signal is acquired from muscles in the torso, the electrocardiography (ECG) signal coming from heart activity can interfere. As a result, the EMG signal can be contaminated during data collection. In this paper, a technique based on discrete stationary wavelet transform (DSWT) is proposed to remove ECG interference from the EMG signal while taking into account the signal-to-noise ratio (SNR). The contaminated EMG signal is decomposed using 5-level DSWT with the Symlet wavelet function. The coefficients for levels 4 and 5, which are contaminated by ECG, are set t

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Zhang, Dan, and Wen Tao Sui. "Noise Reduction of ECG Signal Based on Morphological Filtering and WT." Key Engineering Materials 439-440 (June 2010): 12–16. http://dx.doi.org/10.4028/www.scientific.net/kem.439-440.12.

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In order to eliminate the noise in ECG signal and increase the diagnosis efficiency, a method based on morphological filtering and wavelet algorithm is proposed. The morphological filters is used to filter out the baseline interference signal, and the wavelet transform is applied to remove high frequency interference. The experiment proves that the algorithm is effective.

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Chen, Chi-Chun, Shu-Yu Lin, and Wen-Ying Chang. "Novel Stable Capacitive Electrocardiogram Measurement System." Sensors 21, no. 11 (2021): 3668. http://dx.doi.org/10.3390/s21113668.

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This study presents a noncontact electrocardiogram (ECG) measurement system to replace conventional ECG electrode pads during ECG measurement. The proposed noncontact electrode design comprises a surface guard ring, the optimal input resistance, a ground guard ring, and an optimal voltage divider feedback. The surface and ground guard rings are used to reduce environmental noise. The optimal input resistor mitigates distortion caused by the input bias current, and the optimal voltage divider feedback increases the gain. Simulated gain analysis was subsequently performed to determine the most s

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Hoang, Van Manh, and Manh Thang Pham. "Adaptive Noise Filter for Real-Time Stress ECG Signal Analysis." Journal of Science and Technology - Technical Universities 30.8, no. 147 (2020): 59–64. http://dx.doi.org/10.51316/30.8.10.

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The stress Electrocardiogram (ECG) gives more efficient results for the diagnosis of cardiovascular diseases, which may not be apparent when the patients are at rest. However, the noise produced by the movement of the patient and the environment often contaminates the ECG signal. Motion artifact is the most prevalent and difficult type of interference to filter in stress test ECG. It corrupts the quality of the desired signal thus reducing the reliability of the stress test. In this work, we first describe a quantitative study of adaptive filtering for processing the stress ECG signals. The pr

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Dotsinsky, Ivan, Todor Stoyanov, and Georgy Mihov. "Power-line Interference Removal from High Sampled ECG Signals Using Modified Version of the Subtraction Procedure." International Journal Bioautomation 24, no. 4 (2020): 381–92. http://dx.doi.org/10.7546/ijba.2020.24.4.000802.

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The acquired ECG signals are often contaminated by residual Power-line Interference (PLI). A lot of methods, algorithms and techniques for PLI reduction have been published over the last few decades. The so called subtraction procedure is known to eliminate almost totally the interference without affecting the signal spectrum. The goal of our research was to develop a heuristic version of the procedure intended for ECG signals with high Sampling Rate (SR) up to 128 kHz. The PLI is extracted from the corrupted signal by technique similar to second order band-pass filter but with practically zer

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Oo, Thandar, and Pornchai Phukpattaranont. "Signal-to-Noise Ratio Estimation in Electromyography Signals Contaminated with Electrocardiography Signals." Fluctuation and Noise Letters 19, no. 03 (2020): 2050027. http://dx.doi.org/10.1142/s0219477520500273.

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When electromyography (EMG) signals are collected from muscles in the torso, they can be perturbed by the electrocardiography (ECG) signals from heart activity. In this paper, we present a novel signal-to-noise ratio (SNR) estimate for an EMG signal contaminated by an ECG signal. We use six features that are popular in assessing EMG signals, namely skewness, kurtosis, mean average value, waveform length, zero crossing and mean frequency. The features were calculated from the raw EMG signals and the detail coefficients of the discrete stationary wavelet transform. Then, these features are used

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Wang, Ching Sung, Chien Wei Liu, and Teng Hui Wang. "Implement a Low Noise Portable ECG Circuit." Advanced Materials Research 301-303 (July 2011): 1327–32. http://dx.doi.org/10.4028/www.scientific.net/amr.301-303.1327.

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The most important operation of electrocardiogram (ECG) signal measurement device is to amplify signal and maintain correct original signal. The operation of all circuits cause electromagnetic interference (EMI), but EMI can be reduced by using special component or some PCB layout approaches. This paper provides an example of portable ECG device to demonstrate a method that can effectively reduce EMI and be applied in finished product. This research has built a lead-1 ECG to reach a low noise operation. This result can be easily applied to portable ECG measurement.

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Dolinsky, Pavol, Imrich Andras, Linus Michaeli, and Jan Saliga. "An ECG signal model based on a parametric description of the characteristic waves." ACTA IMEKO 9, no. 2 (2020): 3. http://dx.doi.org/10.21014/acta_imeko.v9i2.760.

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This article introduces a new electrocardiogram (ECG) signal model based on geometric signal properties. Instead of the artificial functions used in common ECG models, the proposed model is based on the modelling of real ECG signals divided into time segments. Each segment has been modelled using simple geometrical forms. The final ECG signal model is represented by the sequence of parameters of the base functions. Parameter variations allow for the generation of different waveforms for each subsequent heartbeat without mixing up the PQRST waves order. Two basic models utilize slightly modifie

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Aqil, Mounaim, Atman Jbari, and Abdennasser Bourouhou. "ECG Signal Denoising by Discrete Wavelet Transform." International Journal of Online Engineering (iJOE) 13, no. 09 (2017): 51. http://dx.doi.org/10.3991/ijoe.v13i09.7159.

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<p>The denoising of electrocardiogram (ECG) represents the entry point for the processing of this signal. The widely algorithms for ECG denoising are based on discrete wavelet transform (DWT). In the other side the performances of denoising process considerably influence the operations that follow. These performances are quantified by some ratios such as the output signal on noise (SNR) and the mean square error (MSE) ratio. This is why the optimal selection of denoising parameters is strongly recommended. The aim of this work is to define the optimal wavelet function to use in DWT decom

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Srinivasa M.G. and Pandian P.S. "Elimination of Power Line Interference in ECG Signal Using Adaptive Filter, Notch Filter and Discrete Wavelet Transform Techniques." International Journal of Biomedical and Clinical Engineering 8, no. 1 (2019): 32–56. http://dx.doi.org/10.4018/ijbce.2019010103.

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An ECG is a biomedical non-stationary signal, which contains valuable information about the electrical activity of the heart. The ECG is very sensitive and a weak signal, hence, it gets corrupted by various types of noise such as power line interference, baseline wander, motion artifacts, muscle contractions, electrode contact noise, etc., that may lead to a misdiagnosis. Among these noise parameters the power line interference is very crucial because noise falls in the ECG bandwidth, i.e. 0.05 Hz to 100 Hz. The article proposes the removal of power line interference (PLI) noise in an ECG sign

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Gupta, Varun, Gavendra Singh, Rohit Sharma, and Sharvan Kumar Pahuja. "Artifact Removal from ECG Signal Using Notch Filter for Developing Countries." Advanced Materials Research 403-408 (November 2011): 120–26. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.120.

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In an increasingly noisy society, methods of reducing noise are becoming more important. Filtering has the great importance in the field of the biomedical signal processing. In many applications of signal processing it is desired to remove sinusoidal interferences while leaving the broadband signal unchanged. Examples are in the areas of communication, control, biomedical engineering and others. A typical one is to cancel 60 Hz power line interference in the recording of electrocardiogram (ECG). Usually this task can be achieved by the notch filters characterized by a unit gain at all frequenc

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Leski, Jacek M. "Robust nonlinear aggregation operator for ECG powerline interference reduction." Biomedical Signal Processing and Control 69 (August 2021): 102675. http://dx.doi.org/10.1016/j.bspc.2021.102675.

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Fathima, S. Yasmin, G. V. S. Karthik, M. Zia Ur Rahman, and A. Lay-Ekuakille. "Efficient Artifact Elimination in Cardiac Signals using Variable Step Size Adaptive Noise Cancellers." International Journal of Measurement Technologies and Instrumentation Engineering 2, no. 1 (2012): 35–51. http://dx.doi.org/10.4018/ijmtie.2012010103.

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In this paper several variable step size adaptive filter structures for extracting high resolution electrocardiographic (ECG) signals are presented which estimates the deterministic components of the ECG signal and removes the artifacts. The noise canceller minimizes the mean square error (MSE) between the input noisy ECG signal and noise reference. Different noise canceller structures are proposed to remove diverse forms of artifacts: power line interference, baseline wander, muscle artifacts and electrode motion artifacts. The proposed implementation is suitable real time applications, where

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Abdullah, Ahmed Kareem, Ahmed Ghanim Wadday, and Ali A. Abdullah. "Separation Enhancement of Power Line Noise from Human ECG Signal Based on Stone Technique." Journal of Biomimetics, Biomaterials and Biomedical Engineering 40 (February 2019): 71–78. http://dx.doi.org/10.4028/www.scientific.net/jbbbe.40.71.

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The cardiac signal is very important for the heart disease diagnosis and evaluation. The noise cancelation represent one of the most preprocessing step in ECG signal processing, usually, this signal is very sensitive and varies with time. The ECG signal is mostly contaminated by different signals like Power line noise signal, Baseline signal and muscle signal. The power line interference signal is the most effected signal on the ECG during data recording. Several papers try to cancel the noise based on different ways and to extract the useful information. In this paper a novel approach based o

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Xu, Lin, Elisabetta Peri, Rik Vullings, Chiara Rabotti, Johannes P. Van Dijk, and Massimo Mischi. "Comparative Review of the Algorithms for Removal of Electrocardiographic Interference from Trunk Electromyography." Sensors 20, no. 17 (2020): 4890. http://dx.doi.org/10.3390/s20174890.

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Surface electromyogram (EMG) is a noninvasive measure of muscle electrical activity and has been widely used in a variety of applications. When recorded from the trunk, surface EMG can be contaminated by the cardiac electrical activity, i.e., the electrocardiogram (ECG). ECG may distort the desired EMG signal, complicating the extraction of reliable information from the trunk EMG. Several methods are available for ECG removal from the trunk EMG, but a comparative assessment of the performance of these methods is lacking, limiting the possibility of selecting a suitable method for specific appl

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Liang, Guo Zhuang, Su Fang Sun, and Jing Xia Wei. "An Approach Based on Wavelet Transform to Remove the Noises of ECG." Advanced Materials Research 562-564 (August 2012): 1899–902. http://dx.doi.org/10.4028/www.scientific.net/amr.562-564.1899.

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In the acquisition process of ECG, noise, which mainly consists of power line interference baseline drift and the EMG interference, often exists due to the instrument, the human body and other aspects. This noise mixed with the ECG, will causes ECG distortion, which makes the whole ECG waveform blurred, and impacts the subsequent signal processing and analysis. In this paper, Coif4 wavelet is used to make the ECG decomposed by 8 scale; at the same time, the wavelet decomposition and reconstruction method is used to remove baseline drift, and then the improved wavelet threshold method is used t

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Hidayat, Rahmad, Ninik Sri Lestari, Herawati Herawati, Givy Devira Ramady, Sudarmanto Sudarmanto, and Farhan Adani. "An approach of adaptive notch filtering design for electrocardiogram noise cancellation." Indonesian Journal of Electrical Engineering and Computer Science 22, no. 3 (2021): 1303. http://dx.doi.org/10.11591/ijeecs.v22.i3.pp1303-1311.

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An electrocardiogram (ECG) is a means of measuring and monitoring important signals from heart activity. One of the major biomedical signal issues such as ECG is the issue of separating the desired signal from noise or interference. Different kinds of digital filters are used to distinguish the signal components from the unwanted frequency range to the ECG signal. To address the question of noise to the ECG signal, in this paper the digital notch filter IIR 47 Hz is designed and simulated to demonstrate the elimination of 47 Hz noise to obtain an accurate ECG signal. The full architecture of t

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Fedotov, A. A. "Analysis of parameters for smoothing electrocardiographic signals Aleksandr A. Fedotov." Izmeritel`naya Tekhnika, no. 12 (December 2019): 47–51. http://dx.doi.org/10.32446/0368-1025it.2019-12-47-51.

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The article is devoted to the consideration of the features of smoothing filtering of ECG signal against the background of electromyographic distortions of various magnitude. The main goal of the research is comparative analysis of various options for the implementation of smoothing filtering of an ECG signal contaminated by myographic interference in order to determine the optimal approach in terms of minimizing biosignal distortions and measurement errors of its amplitude-time characteristics. To obtain quantitative characteristics of effectiveness of various methods for smoothing filtering

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Wu, Lu, Xiaoyun Xie, and Yinglong Wang. "ECG Enhancement and R-Peak Detection Based on Window Variability." Healthcare 9, no. 2 (2021): 227. http://dx.doi.org/10.3390/healthcare9020227.

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In ECG applications, the correct recognition of R-peaks is extremely important for detecting abnormalities, such as arrhythmia and ventricular hypertrophy. In this work, a novel ECG enhancement and R-peak detection method based on window variability is presented, and abbreviated as SQRS. Firstly, the ECG signal corrupted by various high or low-frequency noises is denoised by moving-average filtering. Secondly, the window variance transform technique is used to enhance the QRS complex and suppress the other components in the ECG, such as P/T waves and noise. Finally, the signal, converted by wi

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Manosueb, Anchalee, Jeerasuda Koseeyaporn, and Paramote Wardkein. "PLI Cancellation in ECG Signal Based on Adaptive Filter by Using Wiener-Hopf Equation for Providing Initial Condition." Computational and Mathematical Methods in Medicine 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/471409.

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This paper presents a technique for finding the optimal initial weight for adaptive filter by using difference equation. The obtained analytical response of the system identifies the appropriate weights for the system and shows that the MSE depends on the initial weight. The proposed technique is applied to eliminate the known frequency power line interference (PLI) signal in the electrocardiogram (ECG) signal. The PLI signal is considered as a combination of cosine and sine signals. The adaptive filter, therefore, attempts to adjust the amplitude of cosine and sine signals to synthesize a ref

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Li, Guo Jun, Shu Ting Zhang, Nan Xiao, and Xiao Na Zhou. "Tracking Time-Varying Powerline Interference in Electrocardiogram Using Robust Extended Kalman Filter." Applied Mechanics and Materials 155-156 (February 2012): 127–32. http://dx.doi.org/10.4028/www.scientific.net/amm.155-156.127.

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Powerline interference (PLI) often exhibits variations in frequency and amplitude, whose frequency lies in the spectrum range of the ECG signal. Most previous attempts of tracking time-varying PLI signal are based on Least Squared (LS) algorithm. This makes their methods susceptible to QRS complex in tracking low-level PLI signal. This study presents a new robust Kalman filter-based PLI suppressor to overcome the limitation of existing methods. M-estimation is incorporated into the kalman filter to combat the adverse effect of QRS impulsive. Simulation results indicate that our method outperfo

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Mian Qaisar, Saeed. "Baseline wander and power-line interference elimination of ECG signals using efficient signal-piloted filtering." Healthcare Technology Letters 7, no. 4 (2020): 114–18. http://dx.doi.org/10.1049/htl.2019.0116.

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Strzecha, Krzysztof, Marek Krakós, Bogusław Więcek, et al. "Processing of EMG Signals with High Impact of Power Line and Cardiac Interferences." Applied Sciences 11, no. 10 (2021): 4625. http://dx.doi.org/10.3390/app11104625.

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This work deals with electromyography (EMG) signal processing for the diagnosis and therapy of different muscles. Because the correct muscle activity measurement of strongly noised EMG signals is the major hurdle in medical applications, a raw measured EMG signal should be cleaned of different factors like power network interference and ECG heartbeat. Unfortunately, there are no completed studies showing full multistage signal processing of EMG recordings. In this article, the authors propose an original algorithm to perform muscle activity measurements based on raw measurements. The effective

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Garcia-Casado, Javier, Jose L. Martinez-de-Juan, and Jose L. Ponce. "Adaptive filtering of ECG interference on surface EEnGs based on signal averaging." Physiological Measurement 27, no. 6 (2006): 509–27. http://dx.doi.org/10.1088/0967-3334/27/6/005.

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