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Bivariate AR spectral analysis may quantify autonomic influences on HR/BP signals; leaves open clinical adoption pending validation studies.
A parametric method for autoregressive (AR) auto- and cross-spectral analysis is presented for the contemporaneous processing of heart rate and arterial blood pressure variability signals. In particular, the introduced bivariate spectral analysis (phase and coherence spectra) provides quantitative and objective means which are useful to measure the role played by the neural controlling systems (sympathetic and parasympathetic systems) on the cardiovascular signals under different pathophysiological conditions. Algorithmic aspects, connected to the way of processing discrete numerical series synchronized to single cardiac beats, are particularly stressed. Important applications are foreseen both in physiological studies and in clinical practice as an aid to the detection of various relevant cardiovascular pathologies such as hypertension and diabetes.
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加藤 et al. (2013) studied this question.
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