Efficient and Effective Scheme for ECG Compression

Ali, Alaa Maieed; Ahmed, Anas Fouad; Najim, Ahmed Haitham

doi:10.1109/aicis51645.2020.00024

Cited by 5 publications

(5 citation statements)

References 22 publications

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“…SNRimp is the improvement in the SNR levels between the input and the output. The performance evaluation criteria can be defined as follows [5,22]:…”

Section: Performance Metrics Of Ecg Signal Filtering Approachesmentioning

confidence: 99%

A review of ECG signal filtering approaches

Ahmed¹,

Al-Obaidi²

2022

Global J. Eng. Technol. Adv.

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An electrocardiogram (ECG) quantifies the electrical activity of the heart to screen for different heart diseases, although it can be impacted by noise. ECG signal filtering is a crucial pre-processing step that reduces noise and emphasizes the characteristic waves in ECG data. In real-world applications, the ECG signal is contaminated by different types of noise. Separating the desired signal from noises produced by artifacts such as muscle noise, power line interference (PLI), baseline wandering (BW), and motion artifacts (MA) is a complicated task. In this paper, a quick review of various ECG signal denoising methods is introduced.

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“…SNRimp is the improvement in the SNR levels between the input and the output. The performance evaluation criteria can be defined as follows [5,22]:…”

Section: Performance Metrics Of Ecg Signal Filtering Approachesmentioning

confidence: 99%

A review of ECG signal filtering approaches

Ahmed¹,

Al-Obaidi²

2022

Global J. Eng. Technol. Adv.

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show abstract

“…An electrocardiogram (ECG) is a visual representation of the heart's electrical activity, providing valuable information about its health 1,2 . It has been widely employed in the diagnosis of cardiovascular diseases 3–6 . Figure 1 illustrates the typical shape of an ECG signal, highlighting its key distinguishing features.…”

Section: Introductionmentioning

confidence: 99%

“…1,2 It has been widely employed in the diagnosis of cardiovascular diseases. [3][4][5][6] Figure 1 illustrates the typical shape of an ECG signal, highlighting its key distinguishing features. During heartbeat analysis, noise cancelation is a crucial step.…”

Section: Introductionmentioning

confidence: 99%

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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“…Additionally, combining EOG signals with other modalities like electromyography (EMG) and electroencephalography (EEG) creates additional opportunities for study and application. The integration of these signals enables the creation of cutting-edge human-machine interfaces and offers a more thorough understanding of human behavior [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

A review for filtering techniques of the Electrooculography (EOG) signals

Aws M Abdullah,

Ali R Ibrahim,

Ammar A Al-Hamadani

et al. 2023

Global J. Eng. Technol. Adv.

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Electrooculography (EOG) is a non-invasive method employed for the measurement of the electrical potential produced by ocular movements. EOG signals frequently encounter contamination from diverse forms of interference, thereby impeding precise analysis and interpretation. In order to address these obstacles, numerous filtering methodologies have been devised to ameliorate the quality of EOG signals. The objective of this paper is to examine the filtering techniques commonly employed for EOG signals, elucidating their respective benefits and limitations.

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Efficient and Effective Scheme for ECG Compression

Cited by 5 publications

References 22 publications

A review of ECG signal filtering approaches

A review of ECG signal filtering approaches

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

A review for filtering techniques of the Electrooculography (EOG) signals

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