R-Wave Detection in ECG QRS Complex Using Adaptive Threshold and Window-Based Techniques

This document discusses a critical step in ECG signal processing: R-wave detection within QRS complexes. The author details a threshold-based approach for R-wave identification, implementing an adaptive threshold modification strategy to accommodate waveform variations across different ECG signals. The algorithm dynamically adjusts detection parameters based on signal characteristics, typically using moving averages or percentile-based calculations. Additionally, the author introduces a domain windowing technique for R-wave amplitude localization, which effectively reduces signal-to-noise ratio while enhancing detection accuracy and stability through focused signal analysis within optimized time windows. By integrating these techniques - including potential code implementations using peak detection functions and sliding window algorithms - the system achieves more precise QRS complex R-wave detection, providing robust support for ECG signal analysis and diagnostic applications.