Wigner-Ville analysis and classification of electrocardiograms during thrombolysis

I Chouvarda1, N Maglaveras, A Boufidou

  • 1Laboratory of Medical Informatics, Medical School, Aristotelian University of Thessaloniki, Greece.

Insights

This study uses Wigner-Ville distribution to analyze electrocardiograms (ECGs) after thrombolysis for acute myocardial infarction. The novel iterative method accurately distinguishes successful from unsuccessful thrombolysis, improving patient outcome prediction.

Area of Science:

  • Biomedical Engineering
  • Cardiology
  • Signal Processing

Background:

  • Acute myocardial infarction (AMI) requires timely reperfusion therapy.
  • Electrocardiograms (ECGs) provide crucial diagnostic information.
  • Non-stationary signal analysis offers advanced insights into cardiac dynamics.

Purpose of the Study:

  • To evaluate the effectiveness of Wigner-Ville distribution for analyzing ECGs in patients post-thrombolysis.
  • To differentiate between successful and unsuccessful thrombolysis outcomes using time-frequency ECG features.
  • To develop a predictive model for assessing thrombolysis success.

Main Methods:

  • Analysis of lead V1 Holter ECG recordings from AMI patients undergoing thrombolysis.
  • Application of Wigner-Ville distribution for time-frequency ECG analysis.
  • Feature extraction from time-frequency representations and linear discriminant analysis.
  • Comparison of standard statistical methods with an iterative prediction approach.

Main Results:

  • An iterative prediction method achieved significantly lower classification error (3.8%) compared to standard methods (18.1%).
  • Statistically significant ECG features were identified in QRS, ST, and T-wave segments across various frequency bands.
  • The prediction index evolution over 12 hours differed between successful and unsuccessful thrombolysis groups.

Conclusions:

  • Wigner-Ville distribution and iterative analysis provide a robust method for predicting thrombolysis success in AMI.
  • Distinct time-frequency ECG patterns correlate with treatment outcomes.
  • The dynamic changes in ECGs post-thrombolysis offer insights into cardiac system recovery.

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