You will find interactive Jupyter notebooks for analyzing electrocardiogram (ECG) recordings. These notebooks range from basic to non-linear techniques. There are three folders, one for images used in the notebooks, another for sample ECG recordings and one for the notebooks in a lighter pdf version. The content available in each notebook is:
- Basics: How to identify P wave, QRS complex or T wave? How to measure heart frequency.
- MIT-BIH data: Uses data from the MIT-BIH database available on Physionet.
- Phase space reconstruction: An introduction of Taken's theorem for reconstructing phase space.
- Phase space reconstruction with ECG and Poincaré plots: Applies the last notebook in the ECG time series.
- Animations in phase space: Provides a clearer perspective in which phase space is reconstructed through animations.
- Recurrence plot: Analysis of the ECG with recurrence plots.
- Rest vs. exercise: Comparison in one individual of two time series, before and after doing exercise. Uses previous techniques.
- Batch processing rest vs. exercise: Comparison of several individuals, before and after doing exercise.
- Batch processing with meditation data: Comparison of several recordings with different meditation techniques.
- R-R intervals time series: Phase space reconstruction and recurrence plot with R-R time series.
In case you have any suggestions or questions regarding this repository, do not hesitate to contact [email protected]