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Rolling (time-resolved) DFA alpha1

Source: R/ecg-hrv-nonlinear.R
ecgDFArolling.Rd

Computes the short-range detrended-fluctuation scaling exponent (alpha1) over a sliding window of beats, yielding a time-resolved alpha1 trajectory. This is the basis of the DFA-a1 exercise-intensity thresholds of Gronwald & Rogers (2020).

Usage

ecgDFArolling(rr, window_beats = 300, step_beats = 30, short_range = c(4, 16))

Arguments

rr

A data.frame with columns channel and rr_ms.

window_beats

Window length in beats (default 300).

step_beats

Step between successive windows in beats (default 30).

short_range

Scale range (in beats) for alpha1 (default c(4, 16)).

Value

A data.frame with one row per window and columns channel, beat_start, beat_end, beat_center and alpha1.

References

Peng, C.K. et al. (1995). Quantification of scaling exponents. Chaos, 5(1), 82-87. Gronwald, T. & Rogers, B. (2020). Fractal correlation properties of heart rate variability as a biomarker. Frontiers in Physiology, 11, 550572.

See also

ecgDFA, dfaThresholdCrossings

Examples

set.seed(1)
rr <- data.frame(channel = 1L, rr_ms = 800 + cumsum(rnorm(1000, sd = 2)))
traj <- ecgDFArolling(rr, window_beats = 200, step_beats = 50)