EstimatePSDSlope() R function from [RHRV]

Estimate the slope of the Power Spectral Density (PSD).

Estimate the slope of the Power Spectral Density (PSD) of the RR time series.


EstimatePSDSlope(
  HRVData,
  indexFreqAnalysis = length(HRVData$FreqAnalysis),
  indexNonLinearAnalysis = length(HRVData$NonLinearAnalysis),
  regressionRange = NULL,
  doPlot = T,
  main = "PSD power law",
  xlab = "Frequency (Hz)",
  ylab = "Spectrum",
  pch = NULL,
  log = "xy",
  ...
)

Arguments

HRVData: Data structure that stores the beats register and information related to it.
indexFreqAnalysis: An integer referencing the periodogram that will be used for estimating the spectral index.
indexNonLinearAnalysis: An integer referencing the structure that will store the resulting estimations.
regressionRange: Range of frequencies in which the regression will be performed. Default is c(1e-4, 1e-2) Hz.
doPlot: Plot the periodogram and the least-squares fit?
main: Title for the plot.
xlab: Title for the x axis.
ylab: Title for the y axis.
pch: Symbol for the plotting points.
log: A character string which contains "x" if the x axis is to be logarithmic, "y" if the y axis is to be logarithmic and "xy" or "yx" if both axes are to be logarithmic (default).
...: Other arguments for the plotting function.

Returns

The EstimatePSDSlope returns the HRVData structure containing a PSDSlope field storing the spectral index and the proper Hurst exponent.

Details

The power spectrum of most physiological signals fulfils $S(f)=C*f^-B$ (1/f spectrum). This function estimates the $B$ exponent, which is usually referred to as the spectral index.

Note

It should be noted that the PSD must be estimated prior to the use of this function. We do not recommend the use of the AR spectrum when estimating the spectral index.

Examples


## Not run:

data(HRVProcessedData)
# use other name for convenience
HRVData=HRVProcessedData
# Estimate the periodogram
HRVData=CreateFreqAnalysis(HRVData)
HRVData=CalculatePSD(HRVData,1,"pgram",doPlot = T,log="xy")
HRVData=CreateNonLinearAnalysis(HRVData)
HRVData=SetVerbose(HRVData,T)
HRVData=EstimatePSDSlope(HRVData,1,1,
                        regressionRange=c(5e-4,1e-2))
## End(Not run)

References

Voss, Andreas, et al. "Methods derived from nonlinear dynamics for analysing heart rate variability." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 367.1887 (2009): 277-296.

Eke, A., Herman, P., Kocsis, L., & Kozak, L. R. (2002). Fractal characterization of complexity in temporal physiological signals. Physiological measurement, 23(1), R1.

EstimatePSDSlope function