Source Code for ECG QRS Wave Detection

This text introduces source code designed for detecting QRS waves in electrocardiogram (ECG) signals. The implementation utilizes biorthogonal wavelets, which provide excellent time-frequency localization properties ideal for analyzing non-stationary biomedical signals. The algorithm operates through multiple stages: first performing wavelet decomposition to extract high-frequency components containing QRS information, then applying threshold-based peak detection to identify R-wave peaks with precise timing. This approach effectively distinguishes QRS complexes from noise artifacts and other ECG components like P and T waves. The code includes parameter optimization for different sampling rates and signal qualities, making it adaptable to various ECG monitoring systems. Medical professionals and researchers can leverage this implementation to enhance cardiac condition assessment, support clinical diagnoses, and facilitate cardiovascular research. The robustness of this wavelet-based detection method contributes significantly to ECG processing tools, potentially improving healthcare outcomes through more reliable arrhythmia detection and heart rate variability analysis.