Autoregressive frequency analysis of heart-rate variability with noise rejection and robustness methods was successfully tested through simulations and on real data during ischemic episodes.
The activity of the autonomic nervous system is noninvasively studied by means of autoregressive (AR) frequency analysis of the heart-rate variability (HRV) signal. Some methods of noise rejection and robustness for AR recursive identification are presented that make on-line frequency analysis of the heart-rate variability signal more reliable. The performance of the algorithms is first tested through simulations, and then results obtained on real data during ischemic episodes are presented.
Bianchi et al. (Mon,) conducted a other in Ischemic episodes. Autoregressive frequency analysis of heart-rate variability with noise rejection was evaluated on Performance of the algorithms. Autoregressive frequency analysis of heart-rate variability with noise rejection and robustness methods was successfully tested through simulations and on real data during ischemic episodes.
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