ECG signal analysis using modified S-transform

Area of Science:

• Biomedical Engineering
• Signal Processing
• Cardiology

Background:

• Accurate QRS complex detection is crucial for analyzing heart rate variability (HRV).
• Existing transform techniques for QRS detection have limitations.
• Electrocardiogram (ECG) signal noise can impede accurate R-peak identification.

Purpose of the Study:

• To develop and evaluate a modified S-transform algorithm for precise QRS complex detection in ECG signals.
• To improve the accuracy and efficiency of R-peak localization compared to existing methods.
• To assess the performance of the proposed algorithm using key diagnostic metrics.

Main Methods:

• De-noising of the ECG signal.
• Application of a modified S-transform for QRS complex detection.
• Implementation of a search-back mechanism for R-peak verification.
• Performance evaluation using sensitivity, positive predictivity, and accuracy.

Main Results:

• The modified S-transform algorithm achieved high performance metrics: 99.91% sensitivity, 99.91% positive predictivity, and 99.77% overall accuracy.
• The integrated search-back mechanism demonstrated a highly accurate R-peak localization with a narrow range of ±2 samples.
• The proposed method shows significant improvement over previously reported algorithms in terms of accuracy and search range.

Conclusions:

• The modified S-transform is a highly effective tool for accurate QRS complex detection in ECG signals.
• The algorithm offers superior performance in R-peak localization, essential for reliable HRV analysis.
• This approach provides a robust and efficient method for cardiac rhythm monitoring and diagnostics.