Abstract
Cardiovascular variability is the result of the activity of several physiological control mechanisms, which involve different variables and operate across multiple time scales encompassing short term dynamics and long range correlations. This study presents a new approach to assess the multiscale complexity of multivariate time series, based on linear parametric models incorporating autoregressive coefficients and fractional integration. The approach extends to the multivariate case recent works introducing a linear parametric representation of multiscale entropy, and is exploited to assess the complexity of cardiovascular and respiratory time series in healthy subjects studied during postural and mental stress.
Lingua originale | English |
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Titolo della pubblicazione ospite | 2020 11th Conference of the European Study Group on Cardiovascular Oscillations (ESGCO) |
Pagine | 1-2 |
Numero di pagine | 2 |
Stato di pubblicazione | Published - 2020 |
All Science Journal Classification (ASJC) codes
- ???subjectarea.asjc.1700.1706???
- ???subjectarea.asjc.2600.2611???
- ???subjectarea.asjc.2700.2705???
- ???subjectarea.asjc.2700.2718???
- ???subjectarea.asjc.2700.2737???
- ???subjectarea.asjc.3100.3105???