systole.hrv.nonlinear_domain#

systole.hrv.nonlinear_domain(rr: List | ndarray, input_type: str = 'rr_ms') DataFrame[source]#

Extract the non-linear features of 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:
stats

Nonlinear domain summary statistics. * ‘SD1’ : SD1, the standard deviation of the poincare plot orthogonal to the identity line (ms). * ‘SD2’ : SD2, the standard deviation of the poincare plot along the identity line (ms). * ‘recurrence_rate’ : The recurrence rate in the recurrence plot (%). * ‘l_max’ : The maximun diagonal length in the recurrence plot (beats). * ‘l_mean’ : The mean diagonal length in the recurrence plot (beats). * ‘determinism_rate’ : The determinism rate in the recurrence plot (%). * ‘shannon_entropy’ : The Shannon entropy.

Notes

The dataframe containing the summary statistics is returned in the long format to facilitate the creation of group summary data frame that can easily be transferred to other plotting or statistics library. You can easily convert it into a wide format for a subject-level inline report using the py:pandas.pivot_table() function: >>> pd.pivot_table(stats, values=’Values’, columns=’Metric’)

Warning

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

References

[1]

M. Brennan, M. Palaniswami, and P. Kamen. Do existing measures of Poincaré plot geometry reflect nonlinear features of heart rate variability. IEEE Trans Biomed Eng, 48(11):1342–1347, 2001.

[2]

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.