Abstract:Spectral parameters extracted from the heart rate variability (HRV) signal are obtained on a beat-to-beat basis, following a procedure which uses two recursive algorithms. In the first step of the procedure the set of the AR model coefficients is updated each time a new RR value is available. Then from the estimated AR model parameters, the new position of the poles of the model transfer function in the complex z-plane is evaluated and, finally, through a residual calculation, it is possible to calculate the spectral parameters which quantify the control of the autonomic nervous system in assessing the cardiac frequency (i.e., power and frequency of LF and HF components). The whole procedure has first been tested on a simulated time series, in order to evaluate its performance in tracking the dynamic changes during different conditions; next the algorithms were employed in the study of the HRV signal for continuous monitoring of non-stationary conditions.
The study of the on-line fault diagnosis method for induction motor bearing based on AR Model Parameters Identification