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Impedance cardiography signal denoising using discrete wavelet transform

Souhir Chabchoub1, Sofienne Mansouri2, Ridha Ben Salah3

  • 1University of Tunis El-Manar, ISTMT, Laboratory of Biophysics and Medical Technologies, Tunis, Tunisia. chabchoub_souhir@yahoo.fr.

Australasian Physical & Engineering Sciences in Medicine
|July 5, 2016
PubMed

Insights

This study compares wavelet denoising methods for impedance cardiography (ICG) signals. The Daubechies (db8) wavelet family effectively reduces noise, improving cardiovascular disease diagnosis accuracy.

Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Cardiology

Background:

  • Impedance cardiography (ICG) is a non-invasive diagnostic tool for cardiovascular diseases.
  • ICG signal acquisition is susceptible to noise, hindering accurate hemodynamic parameter determination and diagnosis.
  • Inaccurate ICG waveform recognition leads to misdiagnosis of cardiovascular conditions.

Purpose of the Study:

  • To identify the most effective wavelet-based denoising method for impedance cardiography signals.
  • To evaluate and compare various wavelet families for ICG signal noise reduction.
  • To assess the performance of the best wavelet method against traditional filtering techniques.

Main Methods:

  • Tested Haar, Daubechies (db2-db8), Symlet (sym2-sym8), and Coiflet (coif2-coif5) wavelet families for denoising.
  • Compared the optimal wavelet family with Savitzky-Golay and median filtering.
  • Evaluated methods using signal-to-noise ratio (SNR), root-mean-square error (RMSE), and percent-difference root-mean-square (PRD).

Main Results:

  • The Daubechies wavelet family, specifically db8, demonstrated superior performance in noise reduction.
  • Daubechies (db8) outperformed other tested wavelet families and traditional filtering methods.
  • Quantitative metrics (SNR, RMSE, PRD) confirmed the effectiveness of the db8 wavelet.

Conclusions:

  • The Daubechies (db8) wavelet is the most suitable method for denoising impedance cardiography signals.
  • Effective ICG signal denoising enhances the accuracy of hemodynamic parameter calculation.
  • Improved signal quality facilitates more reliable diagnosis of cardiovascular diseases.

Keywords:
DenoisingDiscrete wavelet transformICG signalMedianSavitzky–Golay

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