Abstract
Fetal heart rate complexity was examined on the basis of RR interval time series obtained in the second and third trimester of pregnancy. In each fetal RR interval time series, short term beat-to-beat heart rate changes were coded in 8 bit binary sequences. Redundancies of the 2(8) different binary patterns were reduced by two different procedures. The complexity of these sequences was quantified using the approximate entropy (ApEn), resulting in discrete ApEn values which were used for classifying the sequences into 17 pattern sets. Also, the sequences were grouped into 20 pattern classes with respect to identity after rotation or inversion of the binary value. There was a specific, nonuniform distribution of the sequences in the pattern sets and this differed from the distribution found in surrogate data. In the course of gestation, the number of sequences increased in seven pattern sets, decreased in four and remained unchanged in six. Sequences that occurred less often over time, both regular and irregular, were characterized by patterns reflecting frequent beat-to-beat reversals in heart rate. They were also predominant in the surrogate data, suggesting that these patterns are associated with stochastic heart beat trains. Sequences that occurred more frequently over time were relatively rare in the surrogate data. Some of these sequences had a high degree of regularity and corresponded to prolonged heart rate accelerations or decelerations which may be associated with directed fetal activity or movement or baroreflex activity. Application of the pattern classes revealed that those sequences with a high degree of irregularity correspond to heart rate patterns resulting from complex physiological activity such as fetal breathing movements. The results suggest that the development of the autonomic nervous system and the emergence of fetal behavioral states lead to increases in not only irregular but also regular heart rate patterns. Using symbolic dynamics to examine the cardiovascular system may thus lead to new insight with respect to fetal development.
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More From: Chaos: An Interdisciplinary Journal of Nonlinear Science
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