Nom

SPWVD_Analysis — Performs the analysis of a narrow band component of the RR signal using Smoothed Pseudo Wigner-Ville time-frequency distribution method.

Calling Sequence

results =
    SPWVD_Analysis(RR,aux,freq_sampling,frequency_bounds,filterlength
    [,options])

Parameters

RR
a real vector of length N: The vector of interbeat intervals of the R waves in the electrocardiogram (ms).
aux
It can be:
  • a real vector of length N: an auxiliary signal that will be added to the result for visualization purposes. For example Vt, SBP, DBP, ...
  • an empty matrix [].
freq_sampling
a real positive scalar, the sampling frequency (in Hz) of the signals.
frequency_bounds
a real row vector of length 2: the frequency range of interest (in Hz). See the ??? section for details.
filterlength
a real scalar with integer value: the order of the FIR Hamming band_pass filter. ??? section for details.
options
A struct with possible fields:
  • <term>lowpass</term>: an odd length vector of real numbers. The coefficients of a fir lowpass filter used to smooth the resulting signals. The default value is computed by wfir("lp",195,[0.01 0],"hm",[0,0])
  • <term>timewindowlength</term>: a real scalar with positive integer odd value. The time smoothing window length used in the smoothed pseudo Wigner-Ville distribution. The default value is 77.
  • <term>frequencywindowlength</term>: a real scalar with positive integer odd value. The frequency smoothing window length used in the smoothed pseudo Wigner-Ville distribution. The default value is 75.
  • <term>frequencybins</term> a real scalar which value is a positive power of 2. The number of frequency bins used in the smoothed pseudo Wigner-Ville distribution. The default value is 128.
The results often are not very sensible to the option values around their default values.
results
a typed list with type "RRA" and with the following fields:
  • <term>time</term>: a real row vector of length N, the time discretization associated with the following signals.
  • <term>RR</term>: a real row vector of length N, the given RR signal
  • <term>aux</term>: a real row vector of length N, the given aux signal or the empty matrix.
  • <term>RRfiltered</term>: a real row vector of length N, the shifted band-pass filtered RR signal.
  • <term>IFreq</term>: a real row vector of length N, the instaneous frequency of the RR signal (in Hz).
  • <term>IAmp</term>: a real row vector of length N, the instaneous amplitude of the RR signal.
  • <term>IPow</term>: a real row vector of length N, the instaneous power of the RR signal.
  • <term>IDisp</term>: a real row vector of length N, the instaneous dispersion of the RR signal.

Description

SPWVD_Analysis Performs the analysis of a narrow band component of the RR signal using Smoothed Pseudo Wigner-Ville time-frequency distribution method. It estimates the instaneous frequency, the instanenous amplitude, the instaneous power and the instaneous dispersion of the RR signal.

The returned data are shifted to make their time evolution comparable and easily drawn using the PlotSpectralAnalysis function.

Caution

  • <term>frequency_bounds</term> This argument is used to reduce the signal band around the effective respiratory frequency. the effective respiratory frequency can be estimated using the Time frequency interactive tool.
  • <term>filterlength</term> The value of this parameter has to establish a compromise between the stiffness of the filter and the sensibility to local variations of the signal.

Examples

    d=read(cardiovascularpath()+"demos/DATA/decubitus_03",-1,4)'; //read the data
    freq_sampling=4;
    RR=d(1,:);//RR signal
    Vt=d(3,:);//Tidal Volume  signal

    //narrow band filter
    filterlength=355;
    frequency_bounds=[0.25 1.9];

    result=SPWVD_Analysis(RR,Vt,freq_sampling,frequency_bounds,filterlength);
   
    PlotSpectralAnalysis(result,["RR","Vt"],"decubitus_03 SPWVD")  // Draw results

    //using options
    opt=struct();
    opt.lowpass=wfir("lp",195,[0.1 0]/freq_sampling,"hm",[0,0]);
    result=SPWVD_Analysis(RR,Vt,freq_sampling,frequency_bounds,filterlength);
    PlotSpectralAnalysis(result,["RR","Vt"],"decubitus_03 SPWVD")  // Draw results

    

See Also

CDM_Analysis, CDM_SPWVD_Analysis, PlotSpectralAnalysis, TimeMoments

Authors

Alessandro Monti, INRIA (scicos version)
Serge Steer, INRIA

Bibliography

"Short-term control of the cardiovascular system: modelling and signal analysis", Alessandro Monti , Claire Médigue , Michel Sorine. Rapport de recherche n° 4427 April 12, 2002

"Instantaneous parameter estimation in cardiovascular time series by harmonic and time-frequency analysis", Alessandro Monti , Claire Médigue , Mangin Laurence,IEEE Trans Biomed Eng. 2002 Dec;49(12 Pt 2):1547-56.

"Instantaneous envelope and phase extraction from real signals: Theory, implementation, and an application to EEG analysis". Periklis Y. Ktonasa and Nicola Papp

Used Functions

TimeMoments