Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Filtering of electromyogram artifacts from the electrocardiogram.

I I Christov1, I K Daskalov

  • 1Centre of Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev str., bl. 105, Sofia, Bulgaria.

Medical Engineering & Physics
|March 16, 2000
PubMed
Summary

This study introduces a novel approximation filtering method to reduce electromyogram (EMG) artifacts in electrocardiogram (ECG) signals. The technique dynamically adjusts filtering parameters based on ECG signal slope, effectively suppressing noise while preserving crucial ECG waveform amplitudes.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Beat-to-beat noise removal in non-invasive His-bundle electrocardiogram.

Medical & biological engineering & computing·2004
Same author

Transthoracic defibrillation with chopping-modulated biphasic waveforms.

Journal of medical engineering & technology·2001
Same author

Monitoring of fluctuating airway obstruction and episodes of coughing by thoracic electrical impedance.

Journal of medical engineering & technology·2001
Same author

Dynamic powerline interference subtraction from biosignals.

Journal of medical engineering & technology·2000
Same author

Comparison of heart rate variability spectra using generic relationships of their input signals.

Medical & biological engineering & computing·1999
Same author

Electrocardiogram signal preprocessing for automatic detection of QRS boundaries.

Medical engineering & physics·1999

Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Cardiology

Background:

  • Electromyogram (EMG) artifacts frequently contaminate electrocardiogram (ECG) recordings, posing a challenge for accurate cardiac diagnosis.
  • Traditional methods like low-pass filtering (≥35 Hz) offer limited EMG artifact suppression and can attenuate vital ECG waveform amplitudes (Q, R, S waves).
  • The random nature and spectral overlap of EMG and ECG signals complicate artifact removal when using a single electrode pair.

Purpose of the Study:

  • To develop and evaluate a novel filtering approach for effectively reducing EMG artifacts in ECG signals.
  • To preserve the amplitude and morphology of essential ECG components (QRS complexes) during artifact suppression.
  • To offer an alternative to conventional filtering methods that suffer from limited efficacy and signal distortion.

Related Experiment Videos

Main Methods:

  • Implementation of an approximation filtering technique with dynamically adjusted sample numbers and weighting coefficients.
  • Utilization of a specific slope measure, calculated from the product of tilts of adjacent 10 ms ECG segments, to guide filter adaptation.
  • Comparative analysis of the proposed method against standard filtering techniques for EMG artifact reduction in ECG.

Main Results:

  • The proposed approximation filtering method significantly reduced EMG artifacts in ECG signals.
  • While some QRS complexes showed slight widening, their amplitudes were largely preserved.
  • Conventional low-pass filtering resulted in substantial reduction of QRS amplitudes, unlike the new method.

Conclusions:

  • The novel approximation filtering method provides a superior solution for mitigating EMG artifacts in ECG signals compared to traditional low-pass filtering.
  • This technique effectively balances artifact suppression with the preservation of diagnostically important ECG waveform characteristics.
  • The dynamic adaptation based on ECG slope offers a promising advancement in robust ECG signal processing.