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ECG Signal Denoising Using an Improved Hybrid DWT-ADTF Approach.

Wissam Jenkal¹, Rachid Latif², Mostafa Laaboubi²

¹Laboratory of Systems Engineering and Information Technology (LiSTi), National School of Applied Sciences ENSA, Ibn Zohr University, Agadir, Morocco. w.jenkal@uiz.ac.ma.

Cardiovascular Engineering and Technology

|November 20, 2023

Summary

This study introduces an improved hybrid ECG denoising method using DWT and ADTF, outperforming existing techniques in noise reduction and efficiency. The enhanced approach is suitable for low-cost hardware applications.

Keywords:

ADTF Adaptive parameter DWT ECG Hybrid filter Signal denoising Thresholding process

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Area of Science:

Biomedical Engineering
Signal Processing

Background:

Electrocardiogram (ECG) signals are crucial for diagnosing heart conditions.
ECG signals are susceptible to noise due to their low-frequency characteristics.

Purpose of the Study:

To present an improved hybrid ECG signal denoising approach.
To enhance ECG signal quality for more accurate heart condition diagnosis.

Main Methods:

Developed a hybrid denoising method combining Discrete Wavelet Transform (DWT) and Adaptive Denoising Filtering Technique (ADTF).
Integrated an adaptive parameter into ADTF, utilized soft thresholding with DWT, and employed a mean filter for baseline wander removal.
Incorporated novel denoising measures and evaluated performance using real and synthetic noise from the Noise Stress Test Database (NSTDB).

Main Results:

The proposed method demonstrated superior performance in Signal-to-Noise Ratio improvement (SN Rimp), ઓછા distortion (PRD, MSE), and diagnostic distortion (SINAD) compared to existing methods.
Achieved promising results across various real and synthetic noise scenarios with different Signal-to-Noise Ratio (SNR) levels.
Showcased significantly lower time complexity than compared denoising approaches.

Conclusions:

The improved hybrid ECG denoising method offers superior statistical results for both real and synthetic noises.
The approach exhibits favorable time complexity, making it suitable for integration into low-cost hardware.
This advancement contributes to more reliable and efficient ECG-based cardiac diagnostics.