ECG Signal Processing: Wiener Filtering, QRST Complex Detection, and RR Interval Analysis

This MATLAB implementation focuses on three key ECG signal processing components: Wiener filtering, QRST complex detection, and RR interval analysis. The Wiener filtering algorithm effectively reduces noise interference in raw ECG signals by estimating and minimizing mean square error, resulting in cleaner waveforms for subsequent analysis. QRST complex detection employs peak detection algorithms and waveform characteristic analysis to identify QRS complexes and T waves in electrocardiogram signals, enabling detailed study of cardiac electrical activity patterns. RR interval detection calculates the time intervals between consecutive R-wave peaks using threshold-based or template matching methods, providing crucial data for assessing heart rate stability and variability trends. Through these integrated processing techniques, comprehensive ECG signal analysis can be performed, delivering valuable information for medical diagnosis and cardiovascular research applications.