Time-dependent analysis of autonomic tests

A method based on wigner-ville power spectral density estimation

C. Marchesi, M. Emdin, S. Pola, A. Macerata, L. Bernardi, C. Carpeggiani, J. A. Marin Neto, M. Cipriani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Heart rate variability is currently analysed through the power spectral density (PSD) of the time series of RR interval (tachogram), estimated by either Fourier transform based or parametric methods. The hypothesis of stationarity of the tachogram, implicit in these methods, cannot be assumed when the series are derived during autonomic tests. The PSD estimation based on the Wigner-Ville time frequency distribution (WD) shows the best performance, in terms of time and frequency resolution, among the various techniques that have been devised for computing time dependent PSD estimates. Such a technique has been applied to the analysis of tachograms, derived from multichannel recordings in normal, diabetic and Chagasic individuals stimulated by autonomic tests. The chosen tests were able of eliciting an increase in vagal tone (Valsalva manoeuvre and phenylephrine), or a sympathetic activation and a parasympathetic withdrawal (head-up tilt). The cross terms artefact associated with the WV technique has been effectively reduced by the smoothed WV estimate, trading off artefacts with a slight decrease of time resolution. The spectra of the tachograms obtained by this procedure allowed to achieve an unique characterisation of the evolving tachogram variability, with high time and frequency resolution, in all the autonomic tests.

Original languageEnglish
Title of host publicationStudies in Health Technology and Informatics
Pages115-126
Number of pages12
Volume35
DOIs
Publication statusPublished - 1997
Event3rd International Workshop on Computer Analysis of Blood Pressure and Heart Rate Signals - Florence, Italy
Duration: May 1 1995May 1 1995

Other

Other3rd International Workshop on Computer Analysis of Blood Pressure and Heart Rate Signals
CountryItaly
CityFlorence
Period5/1/955/1/95

Fingerprint

Power spectral density
Artifacts
Time series
Fourier transforms
Chemical activation
Valsalva Maneuver
Phenylephrine
Fourier Analysis
Heart Rate
Head

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

Cite this

Marchesi, C., Emdin, M., Pola, S., Macerata, A., Bernardi, L., Carpeggiani, C., ... Cipriani, M. (1997). Time-dependent analysis of autonomic tests: A method based on wigner-ville power spectral density estimation. In Studies in Health Technology and Informatics (Vol. 35, pp. 115-126) https://doi.org/10.3233/978-1-60750-879-3-115

Time-dependent analysis of autonomic tests : A method based on wigner-ville power spectral density estimation. / Marchesi, C.; Emdin, M.; Pola, S.; Macerata, A.; Bernardi, L.; Carpeggiani, C.; Marin Neto, J. A.; Cipriani, M.

Studies in Health Technology and Informatics. Vol. 35 1997. p. 115-126.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Marchesi, C, Emdin, M, Pola, S, Macerata, A, Bernardi, L, Carpeggiani, C, Marin Neto, JA & Cipriani, M 1997, Time-dependent analysis of autonomic tests: A method based on wigner-ville power spectral density estimation. in Studies in Health Technology and Informatics. vol. 35, pp. 115-126, 3rd International Workshop on Computer Analysis of Blood Pressure and Heart Rate Signals, Florence, Italy, 5/1/95. https://doi.org/10.3233/978-1-60750-879-3-115
Marchesi C, Emdin M, Pola S, Macerata A, Bernardi L, Carpeggiani C et al. Time-dependent analysis of autonomic tests: A method based on wigner-ville power spectral density estimation. In Studies in Health Technology and Informatics. Vol. 35. 1997. p. 115-126 https://doi.org/10.3233/978-1-60750-879-3-115
Marchesi, C. ; Emdin, M. ; Pola, S. ; Macerata, A. ; Bernardi, L. ; Carpeggiani, C. ; Marin Neto, J. A. ; Cipriani, M. / Time-dependent analysis of autonomic tests : A method based on wigner-ville power spectral density estimation. Studies in Health Technology and Informatics. Vol. 35 1997. pp. 115-126
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