Abstract
The authors describe some time-variant algorithms of autoregressive (AR) identification that result in obtaining a new set of AR parameters for each data sample. The performances of the algorithms were tested on simulated series to better understand their capability in tracking abrupt or constant-rate changes in the signal. A power spectrum density was obtained at each sample and a compressed spectrum array (CSA) graph is plotted. The algorithms were then applied in the study of the heart rate variability signal in dogs during coronary occlusion and in human subjects during transient ischemic episodes. Spectral parameters were obtained on a beat-to-beat basis, for a better comprehension of the dynamic role of the autonomic nervous system in this pathology.
Original language | English |
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Title of host publication | Computers in Cardiology |
Publisher | Publ by IEEE |
Pages | 265-268 |
Number of pages | 4 |
ISBN (Print) | 081862485X |
Publication status | Published - 1992 |
Event | Proceedings of the 18th Annual Conference on Computers in Cardiology - Venice, Italy Duration: Sep 23 1991 → Sep 26 1991 |
Other
Other | Proceedings of the 18th Annual Conference on Computers in Cardiology |
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City | Venice, Italy |
Period | 9/23/91 → 9/26/91 |
ASJC Scopus subject areas
- Software
- Cardiology and Cardiovascular Medicine