Representative QRS loop of the VCG record evaluation

Area of Science:

• Biomedical Engineering
• Cardiology
• Signal Processing

Background:

• Vectorcardiography (VCG) provides valuable insights into cardiac electrical activity.
• Preprocessing VCG signals is crucial for accurate analysis and interpretation.
• Existing methods may struggle with noise and beat-to-beat variability in VCG data.

Purpose of the Study:

• To develop and evaluate an algorithm for preprocessing VCG records.
• To generate a representative QRS loop from VCG data.
• To improve the accuracy of VCG analysis for clinical applications.

Main Methods:

• Digital filtering for noise reduction.
• Wavelet-based detection of ECG fiducial points and PQ intervals.
• Spatial alignment, time synchronization (RMSE minimization), and ectopic QRS elimination.
• Calculation of a representative QRS loop as the average of all QRS loops.

Main Results:

• The algorithm was evaluated on 161 VCG records from healthy subjects and patients with myocardial infarction and bundle branch block.
• Maximum relative deviation ranged from 12.2% (healthy) to 19.3% (myocardial infarction).
• Morphologic variability was significantly reduced post-synchronization and ectopic beat elimination (by factors of 0.36-0.41).

Conclusions:

• The proposed algorithm successfully generates a representative QRS loop from VCG records.
• This representative loop facilitates visualization, comparison, and automated classification of VCG data.
• The method offers a robust approach to VCG signal preprocessing for clinical diagnostics.