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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.
Abstract:
Non-stationary analysis of electrocardiograms (ECGs) using Wigner-Ville distribution is presented. Analysis was performed on subjects with acute myocardial infarction who had undergone thrombolysis, in Holter recordings of lead V1. The distinction between successfully and non-successfully thrombolysed patients was evaluated, based on time-frequency features of the Wigner-Ville transformed ECGs at the sixth hour after lysis. Characteristic parameters were extracted from time-frequency areas, and linear discriminant analysis was performed on these parameters, leading to a prediction index to distinguish the two classes. Thirteen features were found statistically significant by t-test and were used for the classification with linear modelling. Out of these features, four corresponded to frequencies lower than 25 Hz and higher than 50 Hz for, roughly, the QRS complex, five features corresponded to all the frequency bands of, roughly, the ST area, and the last four features corresponded to the T-wave. The feature-vector used in linear modelling was iteratively generated, and the iterative prediction found all 18 features significant. The iterative method resulted in better classification than that of the standard statistical procedure (3.8% error against 18.1% with the classic method). The evolution of the prediction index with time for the first 12 h was different for the successfully and non-successfully thrombolysed groups. Specifically, in the successful thrombolysis group, oscillations and variation with time were more obvious, indicating a possible difference in the dynamics of the cardiac system.
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