The Pan–Tompkins algorithm is commonly used to detect QRS complexes in electrocardiographic signals (ECG).
The Pan–Tompkins algorithm applies a series of filters to highlight the frequency content of this rapid heart depolarization and removes the background noise. The paper suggests following pre-processing steps:
- numpy
- Scipy
- Pan_tompkins_algorithm.py is required for using the algorithm. Import it in your working.
- The class needs ECG data and its sampling rate (Hz) as inputs and it returns a signal which can be extended by finding peaks to get heart rate events.
- Check the .ipynb notebook in the repo to get started.