systole.correction.correct_rr#

systole.correction.correct_rr(rr: List | ndarray, extra_correction: bool = True, missed_correction: bool = True, short_correction: bool = True, long_correction: bool = True, ectopic_correction: bool = True, input_type: str = 'rr_ms', verbose: bool = True) → Tuple[ndarray, Tuple[ndarray, ndarray, ndarray, ndarray, ndarray]][source]#

Correct artefacts in RR time series using the method described in [1].

Parameters:

rr: RR intervals (expressed in seconds or miliseconds), boolean peaks vector or peaks indexes. The function will automatically convert the input into RR intervals (ms).
extra_correction: If True (deault), correct extra beats in the RR time series.
missed_correction: If True (deault), correct missed beats in the RR time series.
short_correction: If True (deault), correct short beats in the RR time series.
long_correction: If True (deault), correct long beats in the RR time series.
ectopic_correction: If True (deault), correct ectopic beats in the RR time series.
n_iterations: Number of iterations (artifacts detection and artifacts correction). Defaults to 1.
input_type: The type of input vector. Default is “rr_ms” (a boolean vector where 1 represents the occurrence of R waves or systolic peaks). Can also be “peaks_idx”, the idexs of samples where a peaks is detected, “peaks”, or “rr_s” for vectors of RR intervals expressed in seconds.
verbose: Control the verbosity of the function. Defaults to True.

Returns:

clean_rr, (nMissed, nExtra, nEctopic, nShort, nLong): The corrected RR time series and the number of artefacts corrected.

See also

correct_peaks

Notes

This function will correct artifacts in RR intervals time series (ms) following the method presented in [1]. First, artifacts are labelled using systole.detection.rr_artefacts(). Then, artifacts are corrected in the following order:

Missed heartbeats (add one heartbeat).
Extra heartbeats (remove one heartbeat).
Ectopic heartbeats (interpolate the values of the two heartbeats).
Short heartbeats (interpolate the value of the heartbeat).
Long heartbeats (interpolate the value of the heartbeat).

These steps can be repeated by changing the n_iterations parameter.

When adding or removing an RR interval (missed and extra artefacts), the artefacts arrays are updated accordingly.

References

[1] (1,2)

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

Examples

>>> from systole import import_rr
>>> from systole.correction import correct_rr

>>> # Load an example RR time series
>>> rr = import_rr().rr

>>> corrected_rr, (nMissed, nExtra, nEctopic, nShort, nLong) = correct_rr(rr)
Cleaning the RR interval time series.
... correcting 1 ectopic interval(s).
... correcting 1 long interval(s).