Characterizing the Propagation of Uterine Electrophysiological Signals Recorded with a Multi-Sensor Abdominal Array in Term Pregnancies

Abstract

The objective of this study was to quantify the number of segments that have contractile activity and determine the propagation speed from uterine electrophysiological signals recorded over the abdomen. The uterine magnetomyographic (MMG) signals were recorded with a 151 channel SARA (SQUID Array for Reproductive Assessment) system from 36 pregnant women between 37 and 40 weeks of gestational age. The MMG signals were scored and segments were classified based on presence of uterine contractile burst activity. The sensor space was then split into four quadrants and in each quadrant signal strength at each sample was calculated using center-of-gravity (COG). To this end, the cross-correlation analysis of the COG was performed to calculate the delay between pairwise combinations of quadrants. The relationship in propagation across the quadrants was quantified and propagation speeds were calculated from the delays. MMG recordings were successfully processed from 25 subjects and the average values of propagation speeds ranged from 1.3–9.5 cm/s, which was within the physiological range. The propagation was observed between both vertical and horizontal quadrants confirming multidirectional propagation. After the multiple pairwise test (99% CI), significant differences in speeds can be observed between certain vertical or horizontal combinations and the crossed pair combinations. The number of segments containing contractile activity in any given quadrant pair with a detectable delay was significantly higher in the lower abdominal pairwise combination as compared to all others. The quadrant-based approach using MMG signals provided us with high spatial-temporal information of the uterine contractile activity and will help us in the future to optimize abdominal electromyographic (EMG) recordings that are practical in a clinical setting.

Toward noninvasive monitoring of ongoing electrical activity of human uterus and fetal heart and brain

“…The mechanical contraction of the uterus is commonly measured with tocodynamometry ( Bakker et al, 2010 ). The electrophysiological activity of the uterus, including increase in synchronization of the myometrial activity and propagation of the contractile activity, can be measured either electrically ( Buhimschi et al, 1997 , Terrien et al, 2010 , De Lau et al, 2013 ) or magnetically ( Eswaran et al, 2002 , Ramon et al, 2005 , Escalona-Vargas et al, 2015 , Govindan et al, 2015 ). Although they are quite useful, these analyses have been limited to the sensor level.…”

Comparison of different feature extraction methods for the analysis of uterine magnetomyography signals to predict term labor

“…a) Data Acquisition and Preprocessing Physionet (mmgdb) database comprised of twenty five magnetomyography signals out of which recordings from twenty four subjects used in this work [21]. The signals were recorded with 151 channel SARA (SQUID Array for Reproductive Assessment) system at University of Arkansas for Medical Sciences, Little Rock, USA [12]. The records have subject id and channel labels along with maternal information like cervical dilation, Days to delivery, BMI and Gestation Period.…”

“…The uterine contraction conduction velocity also increases at the onset of labor [11]. Escalona-Vargas et al [12] reported the uterine MMG signals of term pregnancies where the signals were quantified using the quadrant approach. As the electrical activity of the uterus increases at the onset of labor, the frequency and synchronization indices are helpful to understand the parturition process [13].…”

Potential of Wake-Up Radio-Based MAC Protocols for Implantable Body Sensor Networks (IBSN)—A Survey

“…For example, ECG (Electrocardiogram) sensors are highly sensitive to motion artifact, which can hinder its ubiquitous use. To improve the sensor reliability, multi-sensor or sensor array approaches are commonly used [20]. Sensor fusion techniques can then be applied to fuse information from these sensors.…”