MATLAB Implementation of ECG Signal Filtering with Code Examples

In ECG signal filtering and digital signal processing post-class experiments, we can conduct the following practical implementations:

1. Develop an ECG signal filter using MATLAB source code that performs signal preprocessing and noise reduction to enhance signal quality and accuracy. The implementation typically involves using built-in functions like filtfilt() for zero-phase filtering or designing FIR/IIR filters using fdesign.dataset to remove baseline wander and powerline interference.

2. By generating spectrum analysis diagrams using FFT (Fast Fourier Transform) with functions such as fft() and pwelch(), we can examine the frequency components and energy distribution of the signal. This spectral analysis helps investigate frequency-domain characteristics and provides deeper insights into signal properties.

3. Creating filter response plots allows observation of signal transformations under different filter configurations. Using freqz() for frequency response visualization and comparing effects of various filters (Butterworth, Chebyshev, etc.) enables performance evaluation and suitability assessment for specific ECG applications.

Through these experiments, students can comprehensively learn ECG signal filtering and digital signal processing concepts, enhancing both theoretical understanding and practical implementation skills in biomedical signal processing.