Objective:

The diagnosis of labor is currently one of the most difficult problems encountered by obstetrical healthcare providers. A major health problem is the increase in the rate of preterm delivery, which is responsible for 75% of all deaths in newborns. In addition, preterm delivery is associated with several cognitive and health problems in later life and enormous costs for the health system. A better understanding of myometrial activities could help to reduce preterm deliveries and the costs associated with prematurity in the following years. Therefore, the objective of this study was to determine whether using the Hilbert–Huang transform (HHT) to analyze the uterine contraction data would help us gain a better insight of the myometrial activities of the human uterus during pregnancy.

Material and Methods:

Uterine magnetomyographic (MMG) signals were recorded from pregnant patients at gestational ages of 32–38 weeks. The study was approved by the Human Research Advisory Board of the University of Arkansas for Medical Sciences (UAMS) and performed after obtaining written consent from each patient. The recording of transabdominal MMG signals was conducted with the SQUID Array for Reproductive Assessment (SARA, VSM MedTech Inc; Coquitlam, BC, Canada) system, which has 151 primary magnetic sensors allocated approximately 3 cm apart over an area of 850 cm2. The arrangement of sensors is concave in nature and, in a similar lateral distance, spans the maternal abdomen longitudinally from the symphysis pubis to the uterine fundus. The recording times ranged from 12 to 28 min, and the sampling rate was 250 Hz. The data were down-sampled to 25 Hz to reduce the computational complexity and post-processed with a bandpass filter (0.05–1 Hz) because the uterine contraction activity is a band-limited process (0.05–1 Hz). The recordings of one intrauterine pressure catheter (IUPC) dataset and two mother-perceived contraction datasets were compared with the HHT results, and HHT’s potential was explored through the development of a module and a series of experiments. The local energy and the instantaneous frequency derived from the intrinsic mode functions (IMFs) through HHT provide a full energy-frequency-time distribution of the data. Our objective was to determine whether HHT for each channel can help identify and localize contractions in the uterus. Human studies have been reviewed by the appropriate ethics committee and have therefore been performed in accordance with the ethical standards described in an appropriate version of the 1975 Declaration of Helsinki, as revised in 2000.

Results:

After comparing the IUPC and other mother-perceived contraction (STIM) datasets with HHT results, we were able to visually detect contraction locations in the HHT-processed uterine signals. For verification and validation purposes, when we further analyzed the delay time between two signals, the mechanical activity (i.e., IUPC) following the electrical activity (i.e., magnetic signal) was observed. In conclusion, our experimentations using the method introduced here revealed that there is a 75% correlation between the results obtained by HHT and IUPC data.

Conclusion:

This study compared uterine contractions and changes in the intrauterine pressure with results obtained by HHT. In addition, using IUPC data as a validation guide, we showed that the HHT approach can be used for noise removal. There is a need for time-saving and non-subjective automatic contraction detection in the field of prenatal examination.

Keywords: Uterine contraction, myometrium, magnetomyographic activity, Hilbert–Huang transform, empirical mode decomposition, contraction analysis