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

In RHRV: Heart Rate Variability Analysis of ECG Data

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

Description

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

Usage

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.

Details

The power spectrum of most physiological signals fulfils S(f)=Cf^{-\beta} (1/f spectrum). This function estimates the \beta exponent, which is usually referred to as the spectral index.

Value

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

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.

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.

See Also

spectrum,lsp, CalculatePSD.

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)

RHRV documentation built on Oct. 1, 2024, 1:08 a.m.