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Electrocardiogram

Electrocardiogram

An electrocardiogram (ECG or EKG) is a critical diagnostic tool that records the electrical signals produced by the heart during each heartbeat. This recording is achieved through electrodes placed strategically on the arms, legs, and chest. The electrocardiograph amplifies these signals and produces 12 distinct tracings, offering a comprehensive understanding of the heart's electrical activity.
Three major waveforms are present in a typical ECG recording: the P wave, the QRS complex, and...

ECG Interpretation of Rhythms

ECG Interpretation of Rhythms

An electrocardiogram (ECG)graphically represents the heart's electrical activity on ECG paper or a monitor.
Components of the Electrocardiogram
The primary components of a normal ECG waveform in Normal sinus rhythm(NSR) include the P wave, PR interval, QRS complex, ST segment, T wave, and occasionally a U wave.
ECG waveforms are divided by vertical and horizontal lines at standard intervals.
The horizontal axis measures time and rate, and the vertical axis measures amplitude or voltage....

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Stationary wavelet transform based ECG signal denoising method.

Ashish Kumar¹, Harshit Tomar², Virender Kumar Mehla²

¹School of Electronics Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu 600127, India.

ISA Transactions

|January 9, 2021

Summary

This summary is machine-generated.

This study introduces a novel stationary wavelet transform technique for denoising electrocardiogram (ECG) signals, effectively removing noise while preserving crucial signal components for accurate cardiovascular disease diagnosis.

Keywords:

ECG signal denoising Electrocardiogram Heart rate monitoring Stationary wavelet transform Wavelet filter bank

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Published on: September 1, 2014

Area of Science:

Biomedical Engineering
Signal Processing
Cardiology

Background:

Electrocardiogram (ECG) signals are vital for diagnosing cardiovascular diseases.
ECG signals are susceptible to various noise types, including power line interference, baseline wandering, motion artifacts, and electromyogram noise.
The non-stationary nature of ECG signals complicates noise removal.

Purpose of the Study:

To propose and evaluate a novel denoising technique for ECG signals using stationary wavelet transform.
To compare the performance of the proposed technique against other established denoising methods.
To assess the effectiveness of noise reduction and preservation of ECG signal components.

Main Methods:

A stationary wavelet transform-based denoising technique was developed.
Comparative analysis included lowpass filtering, highpass filtering, empirical mode decomposition, Fourier decomposition method, and discrete wavelet transform.
Performance was quantitatively evaluated using signal-to-noise ratio (SNR), percentage root-mean-square difference (PRD), and root mean square error (RMSE).

Main Results:

The proposed stationary wavelet transform technique demonstrated superior performance in denoising ECG signals.
The stationary wavelet transform method preserved more essential ECG signal components compared to other algorithms.
Quantitative metrics confirmed the effectiveness of the proposed technique over conventional methods.

Conclusions:

Stationary wavelet transform is a highly effective method for denoising ECG signals.
The proposed technique offers an improved approach for noise reduction in ECG signal acquisition.
This advancement can lead to more accurate diagnosis of cardiovascular diseases through cleaner ECG data.