Plot subspaces to vivualize short/long and ectopic beats

The artefact detection is based on the method described in 1.

1

Lipponen, J. A., & Tarvainen, M. P. (2019). A robust algorithm for heart rate variability time series artefact correction using novel beat classification. Journal of Medical Engineering & Technology, 43(3), 173–181. https://doi.org/10.1080/03091902.2019.1640306

# Author: Nicolas Legrand <nicolas.legrand@cfin.au.dk>
# Licence: GPL v3

Visualizing artefacts from RR time series

from systole import import_rr
from systole.plots import plot_subspaces
import matplotlib.pyplot as plt

# Import PPG recording as numpy array
rr = import_rr().rr.to_numpy()

_, axs = plt.subplots(ncols=2, figsize=(12, 6))
plot_subspaces(rr, ax=axs);

(<Axes: title={'center': 'Subspace 1 \n (ectopic beats detection)'}, xlabel='Subspace $S_{11}$', ylabel='Subspace $S_{12}$'>, <Axes: title={'center': 'Subspace 2 \n (long and short beats detection)'}, xlabel='Subspace $S_{21}$', ylabel='Subspace $S_{22}$'>)

Visualizing artefacts from the artefact dictionary

from systole.detection import rr_artefacts

# Use the rr_artefacts function to short/long and extra/missed intervals
artefacts = rr_artefacts(rr)

_, axs = plt.subplots(ncols=2, figsize=(12, 6))
plot_subspaces(artefacts=artefacts, ax=axs)

(<Axes: title={'center': 'Subspace 1 \n (ectopic beats detection)'}, xlabel='Subspace $S_{11}$', ylabel='Subspace $S_{12}$'>, <Axes: title={'center': 'Subspace 2 \n (long and short beats detection)'}, xlabel='Subspace $S_{21}$', ylabel='Subspace $S_{22}$'>)

Using Bokeh as plotting backend

from bokeh.io import output_notebook
from bokeh.plotting import show
from systole.detection import rr_artefacts
output_notebook()

show(
    plot_subspaces(
    artefacts=artefacts, backend="bokeh", figsize=400
    )
)