Multivariate models evaluating interactions between blood pressure, heart rate, and other signals offer a more comprehensive approach to assessing cardiovascular regulation than separate analysis.
Multivariate spectral analysis models provide a more comprehensive assessment of autonomic cardiovascular regulation than analyzing blood pressure or heart rate variability alone.
Blood pressure variability includes rhythmic and nonrhythmic fluctuations that, with the use of spectral analysis, appear as clear peaks or broadband power, respectively. This review offers a concise and critical description of the spectral methods most commonly used (fast Fourier transform versus autoregressive modeling, time-varying versus broadband spectral analysis) and an evaluation of their advantages and disadvantages. It also provides insight into the problems that still affect the physiological and clinical interpretations of data provided by spectral analysis of blood pressure and heart rate variability. In particular, the assessment of blood pressure and heart rate spectra aimed at providing indexes of autonomic cardiovascular modulation is discussed. Evidence is given that multivariate models--which allow evaluation of the interactions between changes in blood pressure, heart rate, and other biological signals (such as respiratory activity) in the time or frequency domains--offer a more comprehensive approach to the assessment of cardiovascular regulation than that represented by the separate analysis of fluctuations in blood pressure or heart rate only.
Parati et al. (1995) conducted a review in Cardiovascular regulation. Spectral analysis of blood pressure and heart rate variability was evaluated. Multivariate models evaluating interactions between blood pressure, heart rate, and other signals offer a more comprehensive approach to assessing cardiovascular regulation than separate analysis.