Matlab code

Here you can find Matlab files for the modeling and analysis of cardiovascular signals and their interactions. Please use and re-use them, get in contact for questions or to report any error, and be nice and acknowledge the source.

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1) Assessment of the dynamic interactions between heart rate and arterial pressure by the cross time–frequency analysis: PhysioMeas2012

Here you can find Matlab code to estimate the time course of spectral coherence, phase difference, time delay, baroreflex sensitivity etc. Some examples are also given.

These algorithms have been described, evaluated and used in the study: Orini et al., “Assessment of the dynamic interactions between heart rate and arterial pressure by cross time-frequency analysis”, Physiological Measurement, (2012)

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2) Characterization of the dynamic interactions between cardiovascular signals by time-frequency coherence:  TBME2011

Here you can find:

  • Matlab code to estimate time-frequency coherence by smoothed pseudo Wigner-Ville distribution (TFCspwv.m) and multitaper spectrogram (TFCmtsp.m),
  • Matlab code to estimate the time-frequency resolution of the corresponding spectra (TFspwv_ref.m, TFmtsp_ref.m)
  • Matlab code to estimate threshold functions to assess the statistical significance of coherence estimates (SITH_spwv.m, SITH_mtsp.m, SDTH_spwv.m).
  • Some examples are provided (Example1.m, ExampleFig8.m) .
  • A short PDF tutorial is also available.
  • Note that some of these functions use algorithms from this time-frequency toolbox

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3) Synthesis of HRV signals characterized by predetermined time-frequency structure by means of time-varying ARMA models: BMSPC2011

Here you can find Matlab code to:

  • Estimate signals characterized by predetermined time-frequency structure (HRVsim_TVARMA.m, yield_hrv.m)
  • An instructive example (HRVsim_TVARMA_example.m).

These algorithms have been described, evaluated and used in the study: Orini et al. “Synthesis of HRV signals characterized by predetermined time-frequency structure by means of time-varying ARMA models”, Biomedical signal processing and control, (2012)

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