Preprocessing of ECG Signal QRS Complexes

Preprocessing ECG signals for QRS complex analysis primarily involves two critical steps: signal acquisition and denoising/filtering. Signal acquisition refers to the process of transferring ECG signals from electrocardiogram devices to computers or storage systems. Denoising/filtering employs digital signal processing techniques to remove noise and interference, ensuring clear QRS complex extraction. For signal acquisition, data cables or wireless transmission protocols (such as Bluetooth or Wi-Fi) can be implemented to transfer signals to computational systems. In denoising steps, filtering algorithms like moving average filters, median filters, and wavelet transforms are commonly applied to reduce noise in ECG signals. Moving average filters smooth signals by averaging adjacent samples, while median filters effectively remove spike noise by replacing each point with the median of neighboring values. Wavelet transform techniques provide multi-resolution analysis for separating noise components from physiological signals. These preprocessing steps establish a reliable data foundation for subsequent QRS complex analysis and clinical ECG diagnosis.