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Identification of contractions from Electrohysterography for prediction of prolonged labor

Open Access
|Mar 2022

Figures & Tables

Fig.1

Representation of surface electrode positioning on the abdominal surface.
Representation of surface electrode positioning on the abdominal surface.

Fig. 2

A comparison of contractions detected using the three methods for the same signal. Top represents the filtering method. Middle represents the statistical method. Bottom represents the TKEO method.
A comparison of contractions detected using the three methods for the same signal. Top represents the filtering method. Middle represents the statistical method. Bottom represents the TKEO method.

Fig. 3

Five equi-temporal regions of a contraction
Five equi-temporal regions of a contraction

Fig. 4

The transition patterns of contractions between the states represented in percentage
The transition patterns of contractions between the states represented in percentage

Fig. 5

Representation of the Markov chain correlation coefficients and the dominance of the uterine segment associated with them.
Representation of the Markov chain correlation coefficients and the dominance of the uterine segment associated with them.

Fig. 6

Confusion matrix of the prediction of the prolonged labor for the test data.
Confusion matrix of the prediction of the prolonged labor for the test data.

Algorithm to define threshold to segment contractions identified from the TKEO method_

Defining threshold to segment contractions from TKEO method
1.Obtain the contraction wave from the EHG signals using the TKEO process.
2.A four-minute window of the RMS signal is chosen.
3.Hanning window function is used to eliminate the edge effects.
4.Set Threshold = 1.2*(basal tone + 25% signal range) where Basal tone = mean of 10% of the lowest values.
5.If the sample value > threshold and is true for > 10 seconds, then
6.It is identified as a contraction
7.Else
8.Move to next sample till the last sample in the four-minute window
9.Slide the four-minute window by one minute & repeat steps 3 to 8

TKEO based algorithm to identify contractions_

TKEObased algorithm to identify contractions
1.The unprocessed EHG signals are obtained.
2.A running mean (an averaging filter) filter is applied to suppress the short-term noise.
3.Linear trends or baseline wandering (if observed) is eliminated by detrending the signal.
4.TKEO and z-score is obtained for the detrended signal.
5.A Gaussian-smoothing filter is applied to smoothen the signal.
6.An envelope of the filtered signal is obtained.
7.Contractions identified.

Transition probabilities of arrested/prolonged progress group

StatesState 1State 2State 3State 4State 5
State 10.6670.3331.0000.0000.667
State 20.0670.0000.0000.0000.000
State 30.0670.0000.0000.0000.000
State 40.0000.0000.0001.0000.333
State 50.2000.6670.0000.0000.000

Dominant region of the uterus during contractions_

FeatureGroupUpper uterine segmentLower uterine segment
Normal progress38.94%61.05%
Dominancearrested Prolonged/ progress73.58%26.41%

Transition probabilities of normal progress group_

StatesState 1State 2State 3State 4State 5
State 10.6920.2630.4000.5000.385
State 20.0510.3680.2000.5000.231
State 30.0260.0530.2000.0000.231
State 40.0510.1050.0000.0000.154
State 50.1790.2110.2000.0000.000

The algorithm to calculate the dominant region of the contraction_

1.Bipolar signals BPU and BPL representing the electrical activity specific to the upper and lower uterine segments are calculated.
2.An envelope of the BPU and BPL is obtained by using Hilbert’s transform.
3.The entire duration of contraction is divided into five equal parts 1 to 5.
4.The RMS amplitude is calculated for the upper and the lower bipolar signals for regions 2,3 and 4 (RMS-u2, RMS-u3, RMS-u4 and RMS-l2, RMS-l3, RMS-l4) representing the most substantial part of the contraction.
5.Dominance is calculated for segments 2, 3 & 4 (D2, D3, D4).
6.The upper uterine segment is dominant if D is positive, and the lower uterine segment is dominant if D is negative.
7.The dominance for the entire contraction is considered to be the most common pattern of dominance in segments 2, 3, and 4.
8.End
Language: English
Page range: 4 - 9
Published on: Mar 31, 2022
Published by: University of Oslo
In partnership with: Paradigm Publishing Services
Publication frequency: 1 times per year

© 2022 Santosh N Vasist, Parvati Bhat, Shrutin Ulman, Harishchandra Hebbar, published by University of Oslo
This work is licensed under the Creative Commons Attribution 4.0 License.