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Stabilogram diffusion analysis (Collins & De Luca 1993)

Source: R/posturography.R
stabilogramDiffusion.Rd

Computes the mean square displacement (MSD) of the CoP as a function of the time interval and extracts the short-term and long-term diffusion coefficients and the critical point (the crossover between open-loop and closed-loop postural control). Planar (resultant) and per-axis analyses are returned.

Usage

stabilogramDiffusion(
  cop,
  sampling_rate,
  ap = NULL,
  ml = NULL,
  detrend = c("mean", "none"),
  max_interval = 10,
  short_max = 1,
  long_min = 2.5
)

Arguments

cop, ap, ml, sampling_rate, detrend

As in swayMetrics().

max_interval

Maximum time interval in seconds over which to compute the MSD (default 10, capped at half the record length).

short_max, long_min

Interval boundaries (seconds) for the short-term (default <= 1 s) and long-term (default >= 2.5 s) linear regions used to estimate the diffusion coefficients.

Value

A stabilogram_diffusion object with, per component (planar, ap, ml), the short/long diffusion coefficients, scaling exponents (Hurst) and the critical-point interval and MSD.

References

Collins JJ, De Luca CJ (1993). Exp Brain Res 95:308-318.

See also

swayMetrics()

Examples

set.seed(1)
n <- 3000
cop <- data.frame(cop_x = cumsum(rnorm(n)) * 0.05,
                  cop_y = cumsum(rnorm(n)) * 0.05)
stabilogramDiffusion(cop, sampling_rate = 100)
#> <stabilogram_diffusion>
#>   planar Ds=0.1071 Dl=0.05532 Hs=0.467 Hl=0.367 crit=(2 s, 0.874)
#>   ap     Ds=0.1147 Dl=0.06055 Hs=0.474 Hl=0.335 crit=(2.64 s, 0.611)
#>   ml     Ds=0.09955 Dl=0.0501 Hs=0.459 Hl=0.412 crit=(1.31 s, 0.271)