ECG Signal Preprocessing - Filtering Techniques and Implementation

This article discusses ECG signal preprocessing, which includes high-pass filters, low-pass filters, and 50Hz band-stop filters. Preprocessing refers to a series of signal processing operations performed before ECG signal analysis to reduce noise and interference effects, thereby improving signal quality and accuracy. High-pass filters are implemented to remove low-frequency noise and baseline drift typically using cutoff frequencies around 0.5-1.0 Hz. In MATLAB, this can be achieved using functions like 'highpass' or designing Butterworth filters with 'butter' and 'filtfilt' for zero-phase filtering. Low-pass filters are employed to eliminate high-frequency noise and interference, commonly with cutoff frequencies between 100-150 Hz to preserve QRS complex characteristics. Implementation often involves FIR or IIR filter designs using functions such as 'lowpass' or custom filter design with specified passband and stopband parameters. The 50Hz band-stop filter specifically targets power line interference, which typically occurs at 50Hz frequency. This can be implemented using notch filters with narrow bandwidth (e.g., 49-51 Hz) through functions like 'bandstop' or designing second-order IIR notch filters with precise quality factor control. By performing these preprocessing steps, useful information from ECG signals can be effectively extracted, providing a more reliable data foundation for subsequent analysis and diagnosis. Proper filter parameter selection and implementation ensure minimal signal distortion while maximizing noise reduction.