MATLAB Simulation and Plotting of ECG Signals with Detailed Waveform Analysis

This content covers MATLAB simulation and plotting of ECG signals, which includes P-wave, Q-wave, QRS complex, S-wave, T-wave, and U-wave components. ECG signals serve as crucial tools for monitoring cardiac function and diagnosing heart conditions. The P-wave represents atrial contraction, the Q-wave indicates electrical activity prior to ventricular contraction, the QRS complex corresponds to ventricular contraction, the S-wave signifies ventricular relaxation, the T-wave represents ventricular repolarization, and the U-wave denotes a less common phenomenon. In MATLAB implementation, simulating ECG signals typically involves generating synthetic waveforms using mathematical models like the dynamic ECG model or Fourier series approximations. Key functions used include plot() for visualization, linspace() for time axis generation, and custom waveform generation algorithms that combine Gaussian functions for individual wave components. Proper parameter tuning is essential for realistic simulation, including amplitude adjustments for P-waves (typically 0.1-0.3 mV), QRS complexes (1-3 mV), and timing intervals between waves. Through MATLAB simulation and plotting, researchers can better understand and analyze individual waveform characteristics in ECG signals, thereby assisting medical professionals in accurate diagnosis and treatment planning. The implementation requires appropriate algorithms and parameters to simulate ECG signal generation and dynamic changes, ensuring accurate results. Therefore, familiarity with the ECG plotting process and characteristics of each waveform component is essential for effective cardiac signal analysis. Common techniques include filtering noisy signals using built-in functions like filter() or designing custom digital filters to enhance waveform visibility.