Journal of Healthcare Engineering

Journal of Healthcare Engineering / 2010 / Article

Research Article | Open Access

Volume 1 |Article ID 141289 | 14 pages | https://doi.org/10.1260/2040-2295.1.1.13

Investigation of the Effects of Continuous Low-Dose Epidural Analgesia on the Autonomic Nervous System Using Hilbert Huang Transform

Abstract

Effects of continuous low-dose epidural bupivacaine (0.05-0.1%) infusion on the Doppler velocimetry for labor analgesia have been well documented. The aim of this study was to monitor the activity of the autonomic nervous system (ANS) for women in labor based on Hilbert Huang transform (HHT), which performs signal processing for nonlinear systems, such as human cardiac systems. Thirteen pregnant women were included in the experimental group for labor analgesia. They received continuous epidural bupivacaine 0.075% infusion. The normal-to-normal intervals (NN-interval) were downloaded from an ECG holter. Another 20 pregnant women in non-anesthesia labor (average gestation age was 38.6 weeks) were included in the comparison group. In this study, HHT was used to decompose components of ECG signals, which reflect three different frequency bands of a person's heart rate spectrum (viz. high frequency (HF), low frequency (LF) and very low frequency (VLF)). It was found that the change of energy in subjects without anesthesia was more active than that with continuous epidural bupivacaine 0.075% infusion. The energy values of the experimental group (i.e., labor analgesia) of HF and LF of ANS activities were significantly lower (P < 0.05) than the values of the comparison group (viz. labor without analgesia), but the trend of energy ratio of LF/HF was opposite. In conclusion, the sympathetic and parasympathetic components of ANS are all suppressed by continuous low-dose epidural bupivacaine 0.075% infusion, but parasympathetic power is suppressed more than sympathetic power.

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Copyright © 2010 Hindawi Publishing Corporation. This 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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