Estimated ECG Subtraction method for removing ECG artifacts in esophageal recordings of diaphragm EMG

Jonkman, Annemijn H.; Juffermans, Ricardo; Doorduin, Jonne; Heunks, Leo; Harlaar, Jaap

doi:10.1016/j.bspc.2021.102861

Cited by 13 publications

(12 citation statements)

References 33 publications

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“…Ref. [ 40 ] proposed an improved version of this method by making it adjustable to the amplitude variations. A comparable approach was put forward by [ 41 ] that uses the median instead of the average of the ECG waveforms to obtain the template.…”

Section: Contaminant Reduction Methodsmentioning

confidence: 99%

Reducing Noise, Artifacts and Interference in Single-Channel EMG Signals: A Review

Boyer

Bouyer

Roy

et al. 2023

Sensors

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Electromyography (EMG) is gaining importance in many research and clinical applications, including muscle fatigue detection, control of robotic mechanisms and prostheses, clinical diagnosis of neuromuscular diseases and quantification of force. However, EMG signals can be contaminated by various types of noise, interference and artifacts, leading to potential data misinterpretation. Even assuming best practices, the acquired signal may still contain contaminants. The aim of this paper is to review methods employed to reduce the contamination of single channel EMG signals. Specifically, we focus on methods which enable a full reconstruction of the EMG signal without loss of information. This includes subtraction methods used in the time domain, denoising methods performed after the signal decomposition and hybrid approaches that combine multiple methods. Finally, this paper provides a discussion on the suitability of the individual methods based on the type of contaminant(s) present in the signal and the specific requirements of the application.

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Section: Contaminant Reduction Methodsmentioning

confidence: 99%

Reducing Noise, Artifacts and Interference in Single-Channel EMG Signals: A Review

Boyer

Bouyer

Roy

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…As in the other methods, the ECG waveforms are averaged to estimate the template. [40] proposed an improved version of this method by making it adjustable to the amplitude variations. A comparable approach was put forward by [41] that uses the median instead of the average of the ECG waveforms to obtain the template.…”

Section: Template Estimation Of the Ecg Interference Signalmentioning

confidence: 99%

Reducing Noise, Artifacts and Interference in Single-Channel EMG Signals : A Review

Boyer¹,

Bouyer²,

Roy³

et al. 2023

Preprint

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EMG analysis is becoming increasingly important in many research and clinical applications, including muscle fatigue detection, control of robotic mechanisms and prostheses, clinical diagnosis of neuromuscular diseases and quantification of force. However, electromyographic signals can be contaminated by various types of noise, interference and artifacts, which can lead to misinterpretation of the data acquired using this method. Even assuming best practices, the collected signal may still be altered by such contaminants. The aim of this paper is to review methods employed to reduce contamination of single channel EMG signals. This review is limited to methods performed directly on the measured EMG signal and those that allow total reconstruction of the EMG signal. Subtraction methods used in the time domain, denoising methods performed after signal decomposition and hybrid methods are assessed. It is defended that individual methods may be more or less suitable for a particular application depending on contaminant(s) present in the signal and on the specific requirements of the application.

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“…28 Therefore, if there is previous information about the measured signal, suitable thresholds in various wavelet scales must be computed depending on the characteristics of the frequency spectrum of the signals. Let Ω be the frequency domain of the corrupted signal δ following the decomposition process; the dynamic threshold t hD is suggested to enhance the effectiveness of wavelet denoising, as demonstrated in Equation (8).…”

Section: Universal Threshold and The Proposed Dynamic Thresholdmentioning

confidence: 99%

“…The intensity of noise is generally low during relaxation, but it increases significantly when a person is under stress, posing challenges in extracting clinical information. 8,9 Various types of noise, such as Base-Line Wanders (BL), Electrode Movements (EM), Power-Line Crosstalk (PL), Inappropriate Measuring (IM) environment, Bad Electrode Contact (BE), and Electromyography (EMG) signals, can contaminate the ECG signal during acquisition and transmission. 10,11 While conventional filters can effectively eliminate most of these noise types, extracting a clean heartbeat from an ECG signal corrupted with "Additive White Gaussian Noise" (AWGN) remains a critical issue.…”

Section: Introductionmentioning

confidence: 99%

“…During heartbeat analysis, noise cancelation is a crucial step. The intensity of noise is generally low during relaxation, but it increases significantly when a person is under stress, posing challenges in extracting clinical information 8,9 . Various types of noise, such as Base‐Line Wanders (BL), Electrode Movements (EM), Power‐Line Crosstalk (PL), Inappropriate Measuring (IM) environment, Bad Electrode Contact (BE), and Electromyography (EMG) signals, can contaminate the ECG signal during acquisition and transmission 10,11 .…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An efficient wavelet thresholding strategy and robust shrinkage approach for de‐noising ECG signal

Ahmed

2023

Int J Imaging Syst Tech

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This paper introduces an efficient wavelet thresholding strategy and robust shrinkage approach (WTS) for de‐noising the ECG signals. The optimal mother wavelet for de‐noising the ECG signal is automatically selected based on cross‐correlation and energy‐to‐entropy indices. A dynamic threshold is applied to various levels of decomposition to eliminate different types of noise. A shrinkage approach is suggested to attain seamless on–off transitions. The achievement of the WTS is compared with the state of the art reported in the literature using 180 real ECG signals collected from 60 volunteers. The ECG signals were recorded using three standard ECG machines without applying the filtering option to provide a diverse range of noisy ECG signals. The de‐noising outcomes show that the presented WTS can automatically select the optimal mother wavelet for the particular ECG signal, and it is superior to other techniques in terms of the average predicted signal‐to‐noise ratio (), the average predicted root‐mean‐square error (), and the average execution time (AET).

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Estimated ECG Subtraction method for removing ECG artifacts in esophageal recordings of diaphragm EMG

Cited by 13 publications

References 33 publications

Reducing Noise, Artifacts and Interference in Single-Channel EMG Signals: A Review

Reducing Noise, Artifacts and Interference in Single-Channel EMG Signals: A Review

Reducing Noise, Artifacts and Interference in Single-Channel EMG Signals : A Review

An efficient wavelet thresholding strategy and robust shrinkage approach for de‐noising ECG signal

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