Dynamic detection of rhythmic oscillations in heart-rate tracings: a state-space approach based on fourth-order cumulants.

Abstract

This paper presents a new procedure specifically aimed at providing a dynamical detection of the oscillations occurring in long-term heart-rate (HR) tracings. The procedure is based on a time-variant state-space modelling of the fourth-order cumulants of the HR signal. The state-space estimator was selected because of its demonstrated capability to distinguish between deterministic and stochastic components of the signal, while the fourth-order cumulants of the signal were used as input of the model to further reduce adverse effects of coloured, white and l/f Gaussian noise possibly present in the input data. The procedure was tested by the analysis of simulated signals and its performance was compared with the results obtained by state-space modelling applied directly on the test signals (instead of on the fourth-order cumulants of the signals) and by the more traditional auto-regressive modelling. The comparison has shown a clear superiority of the proposed procedure over the other techniques in discriminating deterministic oscillations from coloured noise. Finally, the applicability of the procedure to biological data was verified by analysing five experimental HR tracings recorded in normal subjects during laboratory and daily life conditions.