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Elimination of ECG Artefacts in Foetal EEG Using Ensemble Average Subtraction and Wavelet Denoising Methods: A Simulation

  • F. Abtahi
  • F. Seoane
  • K. Lindecrantz
  • N. Löfgren
Part of the IFMBE Proceedings book series (IFMBE, volume 41)

Abstract

Biological signals recorded from surface electrodes contain interference from other signals which are not desired and should be considered as noise. Heart activity is especially present in EEG and EMG recordings as a noise. In this work, two ECG elimination methods are implemented; ensemble average subtraction (EAS) and wavelet denoising methods. Comparison of these methods has been done by use of simulated signals achieved by adding ECG to neonates EEG. The result shows successful elimination of ECG artifacts by using both methods. In general EAS method which remove estimate of all ECG components from signal is more trustable but it is also harder for implementation due to sensitivity to noise. It is also concluded that EAS behaves like a high-pass filter while wavelet denoising method acts as low-pass filter and hence the choice of one method depends on application.

Keywords

Noisy Signal Quiet Wakefulness Wavelet Denoising Method IFMBE Proceeding Signal Wavelet Transform 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • F. Abtahi
    • 1
  • F. Seoane
    • 1
    • 3
  • K. Lindecrantz
    • 1
    • 2
  • N. Löfgren
    • 4
  1. 1.School of Technology and HealthKTH Royal Institute of TechnologyStockholmSweden
  2. 2.Department of Clinical Science, Intervention and TechnologyKarolinska InstituteStockholmSweden
  3. 3.School of EngineeringUniversity of BoråsBoråsSweden
  4. 4.Neoventa MedicalMölndalSweden

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