<i>Electrical Activity of the Human Uterus in Labor</i>

Larks, Saul D.; Assali, N.S.; Morton, Daniel G.; Selle, W. A.

doi:10.1152/jappl.1957.10.3.479

Cited by 18 publications

(6 citation statements)

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Section: The Slow Wave Emgmentioning

confidence: 99%

“…Ample researches have identified the slow wave in EHG [6,[57][58][59][60][61][62]. These studies found that the slow wave is measurable in external EHG and its amplitude and frequency corresponds to non-labor uterine contractions [57,60,62]. Nonetheless, the fast wave has been preferred in most studies as the slow wave was considered to be prone to mechanical artifacts such as contact-potential between electrode and skin and other baseline drifts [61,62].…”

Section: The Slow Wave Emgmentioning

confidence: 99%

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Multivariate Time–Frequency Analysis of Electrohysterogram for Classification of Term and Preterm Labor

You

Kim

Seok

et al. 2019

J. Electr. Eng. Technol.

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Non-invasive electrohysterogram (EHG) could be a promising technique for the preterm birth prediction, which could enable us to diagnose the preterm birth before the labor and reduces the infant mortality and morbidity. Previous studies on the preterm birth prediction with EHG have conducted comprehensive researches on various signal features and classification algorithms, but most of them adopted prefilters based on the linear transforms using fixed basis function, although they are suboptimal for the nonlinearity and nonstationarity of the EHG signal. In this paper, multivariate empirical mode decomposition (MEMD) is applied to decompose the electrical activity signal measured on the uterus. After the decomposition, features are calculated for the corresponding oscillations to the uterine contraction. To investigate the performance of the features, three-channel EHG signals of 254 patients (224 term, 30 preterm) are chosen among 300 patients from Physionet term-preterm electrohysterogram (TPEHG) database to extract features from the EHG signals and classify the features using machine learning algorithms. Classification results shows that the proposed method with MEMD achieved 94.66% correctly classified rate (CCR) and 0.987 area under the curve (AUC), which outperformed those with IIR filter implying MEMD provides a new prospect to improve the current preterm birth prediction approach.

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Section: The Slow Wave Emgmentioning

confidence: 99%

Section: The Slow Wave Emgmentioning

confidence: 99%

Multivariate Time–Frequency Analysis of Electrohysterogram for Classification of Term and Preterm Labor

You

Kim

Seok

et al. 2019

J. Electr. Eng. Technol.

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“…One of the first attempts to explain the electrohysterogram was done in 1957 by Larks et al (1957). They concluded that a biphasic pattern-named electrical complex-can be recognized in the abdominal signal recorded.…”

Section: Origin and Propertiesmentioning

confidence: 99%

Quantitative analysis of contraction patterns in electrical activity signal of pregnant uterus as an alternative to mechanical approach

et al. 2005

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Monitoring of uterine contraction activity is an important diagnostic tool used during both pregnancy and labour. The strain the pregnant uterus exerts on the maternal abdomen is measured via external tocography. However, limitation of this approach has caused the development of another technique-electrohysterography--which is based on the recording of electrical uterine activity. A computer-aided system is presented, which allows the recording of electrohysterographic signals from the maternal abdomen and their on-line analysis both in time and frequency domains. As a research material, we acquired 108 traces during a 24 h period before labour from a group of patients between 37 and 40 weeks of gestation. The comparison study between electrohysterography and tocography was carried out thanks to the possibility of simultaneous recording of mechanical and electrical uterine activities. The obtained results show that both methods demonstrate high agreement in relation to the number of contractions recognized as being consistent. However, their agreement in relation to the quantitative description of recognized patterns has appeared to be unacceptable to consider these methods as fully alternative. The appropriate way of further development of electrohysterography seems to be spectral analysis. Several spectral parameters describing electrophysiological properties of uterine muscle can be obtained by the use of electrohysterographic signals.

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“…The first that reported the SW in the EHG was by Dill and Maiden (Dill and Maiden 1946), who performed recordings from both the abdominal and uterine surfaces of pregnant women during labor. A decade later Larks et al (Larks et al 1957, Larks andDasgupta 1958) described the amplitude, duration and shape of SW activity from the abdominal surface. They described it as a regular slow negative deflection preceded by a diphasic complex of the recorded potential with a mean amplitude of 6.74 mV, a duration of several minutes and a period equal to that of the uterine contraction, whose presence was associated with the electrical recovery/repolarization of the uterine muscle.…”

Section: Introductionmentioning

confidence: 99%

Uterine slow wave: directionality and changes with imminent delivery

Albaladejo-Belmonte¹,

Prats-Boluda²,

Ye-Lin³

et al. 2022

Physiol. Meas.

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Objective. The slow wave (SW) of the electrohysterogram (EHG) may contain relevant information on the electrophysiological condition of the uterus throughout pregnancy and labor. Our aim was to assess differences in the SW as regards the imminence of labor and the directionality of uterine myoelectrical activity. Approach. The SW of the EHG was extracted from the signals of the Icelandic 16-electrode EHG database in the bandwidth [5, 30] mHz and its power, spectral content, complexity and synchronization between the horizontal (X) and vertical (Y) directions were characterized by the root mean square (RMS), dominant frequency (domF), sample entropy (SampEn) and maximum cross-correlation (CCmax) of the signals, respectively. Significant differences between parameters at time-to-delivery (TTD) ≤7 vs. >7 days and between the horizontal vs. vertical directions were assessed. Main results. The SW power significantly increased in both directions as labor approached (TTD≤7d vs. >7d (mean±SD): x= 0.12±0.10 vs. 0.08±0.06mV; y= 0.12±0.09 vs. 0.08±0.05mV), as well as the dominant frequency in the horizontal direction (= 9.1±1.3 vs. 8.5±1.2mHz) and the synchronization between both directions (= 0.44±0.16 vs. 0.36±0.14). Furthermore, its complexity decreased in the vertical direction (= 6.13·10−2±8.7·10−3 vs. 6.50·10−2±8.3·10−3), suggesting a higher cell-to-cell electrical coupling. Whereas there were no differences between the SW features in both directions in the general population, statistically significant differences were obtained between them in individuals in many cases. Significance. Our results suggest that the SW of the EHG is related to bioelectrical events in the uterus and could provide objective information to clinicians in challenging obstetric scenarios.

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Electrical Activity of the Human Uterus in Labor

Cited by 18 publications

References 0 publications

Multivariate Time–Frequency Analysis of Electrohysterogram for Classification of Term and Preterm Labor

Multivariate Time–Frequency Analysis of Electrohysterogram for Classification of Term and Preterm Labor

Quantitative analysis of contraction patterns in electrical activity signal of pregnant uterus as an alternative to mechanical approach

Uterine slow wave: directionality and changes with imminent delivery

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