Simulating ECG Data with MATLAB

In this article, I would like to emphasize that simulating ECG signal data using MATLAB is highly beneficial for enhancing comprehension and learning in bioelectrical data processing. Such data simulation provides practical case studies and hands-on opportunities, enabling learners to better master techniques and knowledge in bioelectrical signal processing. By utilizing MATLAB for simulation, learners can actively manipulate and adjust parameters (such as heart rate variability, noise levels, and waveform characteristics), thereby gaining deeper insights into signal processing principles and workflows. Through functions like signal generation tools and filtering algorithms, MATLAB allows for realistic ECG waveform synthesis including P-waves, QRS complexes, and T-waves. This approach facilitates comprehensive learning experiences in feature extraction, arrhythmia simulation, and signal denoising methods. Consequently, working with simulated ECG data establishes a solid foundation for future research and applications in the bioelectrical domain, particularly in biomedical engineering and clinical diagnostics.