ECG Wave Delineation Visualizer

This project visualizes ECG signals with automatic delineation of P, Q, R, S, and T waves using Python. It can process ECG records from PhysioNet or plot your own ECG data from a CSV file.

Features

• Plots RR intervals and provides summary statistics.
• Plots actual ECG data from CSV files with R peak detection and RR interval analysis.

Requirements

• Python 3.7+
• matplotlib
• numpy
• pandas

Install dependencies with:

pip install matplotlib numpy pandas

Usage

1. Clone or download this repository.

To plot your own ECG data from a CSV file:

python plot_actual_data.py

• Expects a data.csv file in the working directory.
• Ignores timestamps in the CSV and generates a time axis based on the sampling rate.
• Inverts the ECG signal for visualization.
• Detects R peaks using a threshold and minimum distance.
• Plots the ECG signal with detected R peaks and the RR intervals over time.
• Prints the sampling rate and the processed DataFrame.

CSV Format:
Your data.csv should have at least the columns TIME (timestamp) and ECG (signal value).

Example:

TIME,ECG
18:00:05.699,661.022705
18:00:05.704,735.636780
18:00:05.709,752.442139
18:00:05.714,592.245361
18:00:05.719,637.751221
18:00:05.724,714.962036
18:00:05.729,579.380798
...

Customization

• To analyze a different record, change the record_name and database variables in test.py.
• Adjust the R peak detection threshold or minimum distance in plot_actual_data.py as needed.
• For plotting your own data, ensure your CSV file is formatted with TIME and ECG columns.

License

This project is for educational purposes.