ECG Data QRS Complex Extraction

In this documentation, we utilize data from the MIT-BIH database as our primary source and perform QRS complex extraction on electrocardiogram (ECG) signals. This represents a critical preprocessing step in ECG analysis, as accurate QRS complex detection enables comprehensive understanding of cardiac activity patterns within electrical heart signals. Through QRS complex extraction, we can derive essential cardiac parameters and features including heart rate variability, cardiac rhythm patterns, and pathological abnormalities. These metrics are vital for diagnosing cardiovascular diseases and monitoring cardiac health status. The implementation typically involves signal processing techniques such as digital filtering to remove noise, derivative-based algorithms for slope detection, and thresholding methods for peak identification. Common approaches include Pan-Tompkins algorithm which employs bandpass filtering, differentiation, squaring, and moving window integration to enhance QRS complexes. Therefore, QRS complex extraction from ECG data constitutes a fundamental and necessary procedure in cardiac informatics.