systole.hrv.recurrence

systole.hrv.recurrence(rr: List | ndarray, input_type: str = 'rr_ms') → Tuple[float, int, float, float, float]

Compute quantitative metrics from the recurrence plot for heart rate variability.

Parameters:

rr

R-R interval time-series, peaks or peaks index vectors. The default expected vector is R-R intervals in milliseconds. Other data format can be provided by specifying the “input_type” (can be “rr_s”, “peaks” or “peaks_idx”).

input_type

The type of input provided. Can be “peaks”, “peaks_idx”, “rr_ms” or “rr_s”. Defaults to “rr_ms”.

Returns:

recurrence_rate

The percentage of recurence in the time series. This corresponds to the ratio of ones and zeros in the recurrence plot.

l_max

Maximum lenght of the diagonale in the reccurence plot.

l_mean

Mean of the diagonals lengths observed in the recurence plot.

determinism_rate

The percentage of determinism in the time series.

shan_entr

Shannon information entropy.

Warning

The recurrence plots results does not reproduce what is obtained using Kubios (3.5.0) and should be used with caution for now.

See also

nonlinear_domain, poincare

References

[1]

H. Dabire, D. Mestivier, J. Jarnet, M.E. Safar, and N. Phong Chau. Quantification of sympathetic and parasympathetic tones by nonlinear indexes in normotensive rats. amj, 44:H1290–H1297, 1998.

[2]

C.L. Webber Jr. and J.P. Zbilut. Dynamical assessment of physiological systems and states using recurrence plot strategies. J Appl Physiol, 76:965–973, 1994.

[3]

Zbilut J. P., Webber C. L., Zak M.Quantification of heart rate variability using methods derived from nonlinear dynamics.Assessment and Analysis of Cardiovascular Function, Drzewiecki G., Li J. K.-J. Springer New York.