| Literature DB >> 12181145 |
Itay Perlstein1, Nir Sapir, Joshua Backon, Dan Sapoznikov, Roman Karasik, Shlomo Havlin, Amnon Hoffman.
Abstract
We studied heart rate variability in rats by power scaling spectral analysis (PSSA), autoregressive modeling (AR), and detrended fluctuation analysis (DFA), assessed stability by coefficient of variation between consecutive 6-h epochs, and then compared cross-correlation among techniques. These same parameters were checked from baseline conditions through acute and chronic disease states (streptozotocin-induced diabetes) followed by therapeutic intervention (insulin). Cross-correlation between methods over the entire time period was r = 0.94 (DFA and PSSA), r = 0.81 (DFA and AR), and r = 0.77 (AR and PSSA). Under baseline conditions the scaling parameter measured by DFA and PSSA and the high-frequency (HF) component measured by AR fluctuated around an average value, but these fluctuations were different for the three methods. After diabetes induction, a strong correlation was found between the HF power and the short-term scaling parameter. Despite their differences in methodology, DFA and PSSA assess changes in parasympathetic tone as detected by autoregressive modeling.Entities:
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Year: 2002 PMID: 12181145 DOI: 10.1152/ajpheart.00519.2001
Source DB: PubMed Journal: Am J Physiol Heart Circ Physiol ISSN: 0363-6135 Impact factor: 4.733