MATLAB Simulation for ECG and PPG Signal Generation

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A MATLAB-based framework for generating customizable ECG and PPG signals with realistic noise artifacts, designed to train and validate signal classification algorithms.

This post introduces a MATLAB-based simulation tool designed to generate synthetic Electrocardiogram (ECG) and Photoplethysmogram (PPG) signals. The primary objective is to create labeled datasets with controlled noise characteristics, which are essential for training and robustly validating signal classification algorithms.

Source Code

The complete source code and modified versions are available below:

Note: The modified version addresses an issue in the original code where PPG signals could not be generated with zero noise. It is recommended to use the modified version for clean signal generation.

Simulation Results: Signal Type 1 (50 RR Intervals)

The following metrics illustrate the time-domain and frequency-domain characteristics of the generated signals under various noise conditions.

Parameters

  • Signal Duration: 50 RR intervals
  • Signal Type: Type 1 (Standard Verification Signal)

1. Noise-Free Baseline

The reference signal without any added noise.

2. Noise Scenario 1

Signal Analysis

Time and frequency domain representation of the signal corrupted by Noise 1.

Component Breakdown

  • Clean Signal Component:
  • Noise Component:
  • Signal-to-Noise Ratio (SNR) Analysis:

3. Noise Scenario 2

Signal Analysis

Component Breakdown

  • Clean Signal Component:
  • Noise Component:
  • SNR Analysis:

4. Noise Scenario 3

Signal Analysis

Component Breakdown

  • Clean Signal Component:
  • Noise Component:
  • SNR Analysis:

5. Noise Scenario 4

Signal Analysis

Component Breakdown

  • Clean Signal Component:
  • Noise Component:
  • SNR Analysis:

Comparative Analysis: Signal Types with 10 RR Intervals

To evaluate short-duration performance, we generated five distinct signal types with a duration of 10 RR intervals.

Type 1

Type 2

Type 3

Type 4

Type 5