Gaussian Modelling Characteristics of Peripheral Arterial Pulse: Difference between Measurements from the Three Trimesters of Healthy Pregnancy

Kunyan Li, Song Zhang, Lin Yang, Hongqing Jiang, Dongmei Hao, Dingchang Zheng

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Abstract

Arterial pulse wave analysis has been attempted to monitor the maternal physiological changes of circulatory system during pregnancy. This study aimed to quantify the difference of Gaussian modelling characteristics derived from radial pulses measured from the three trimesters of healthy pregnant women. Radial pulses were recorded from seventy pregnant women between gestational week 11–13, week 20–22, and then week 37–39. They were then normalized and decomposed into three independent Gaussian waves for deriving four key modelling characteristic parameters: including the peak time interval (T) and peak amplitude ratio (R) between the first and second Gaussian waves (T1,2 and R1,2), and their corresponding values between the first and third Gaussian waves (T1,3 and R1,3). Post hoc multiple comparisons after analysis of variance was then applied to study the within-subject differences in Gaussian modelling characteristics between the three trimesters. The key results were that T1,2 and T1,3 increased significantly (T1,2: 12.8 ± 1.3 vs 13.2 ± 1.3, ; T1,3: 39.5 ± 4.3 vs 45.4 ± 5.1, ), and R1,3 decreased significantly from the first to second trimester (0.60 ± 0.15 vs 0.53 ± 0.11, ). From the second to third trimester, T1,2 decreased significantly (13.2 ± 1.3 vs 12.8 ± 1.2, ), and T1,3 and R1,3 decreased slightly but nonsignificantly. Since larger T1,2 and T1,3 and smaller R1,3 are associated with more compliant peripheral arteries, our results indicated that peripheral arteries become more compliant from the first to second trimester and then have a tendency of returning to baseline during normal pregnancy. In conclusion, this study has quantitatively demonstrated significant changes of Gaussian modelling characteristics derived from radial pulses at the three trimesters of normal pregnant women, suggesting that these modelling characteristics could be used as parameters in monitoring maternal physiological changes during normal pregnancy.

Original languageEnglish
Article number1308419
Number of pages9
JournalJournal of Healthcare Engineering
Volume2018
DOIs
Publication statusPublished - 11 Oct 2018
Externally publishedYes

Bibliographical note

Copyright © 2018 Kunyan Li et al. .is is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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