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Improved Prediction of Preterm Delivery Using Empirical Mode Decomposition Analysis of Uterine Electromyography Signals.

Ren P, Yao S, Li J, Valdes-Sosa PA, Kendrick KM - PLoS ONE (2015)

Bottom Line: Next, the entropy values of both instantaneous amplitude and instantaneous frequency of the first ten IMF components are computed in order to derive ratios of these two distinct components as features.Discrimination accuracy of this approach compared to those proposed previously was then calculated using six differently representative classifiers.Overall, our results show a clear improvement in prediction accuracy of preterm delivery risk compared with previous approaches, achieving an impressive maximum AUC value of 0.986 when using signals from an electrode positioned below the navel.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Biomedicine, University of Electronic Science and Technology of China, Chengdu, China.

ABSTRACT
Preterm delivery increases the risk of infant mortality and morbidity, and therefore developing reliable methods for predicting its likelihood are of great importance. Previous work using uterine electromyography (EMG) recordings has shown that they may provide a promising and objective way for predicting risk of preterm delivery. However, to date attempts at utilizing computational approaches to achieve sufficient predictive confidence, in terms of area under the curve (AUC) values, have not achieved the high discrimination accuracy that a clinical application requires. In our study, we propose a new analytical approach for assessing the risk of preterm delivery using EMG recordings which firstly employs Empirical Mode Decomposition (EMD) to obtain their Intrinsic Mode Functions (IMF). Next, the entropy values of both instantaneous amplitude and instantaneous frequency of the first ten IMF components are computed in order to derive ratios of these two distinct components as features. Discrimination accuracy of this approach compared to those proposed previously was then calculated using six differently representative classifiers. Finally, three different electrode positions were analyzed for their prediction accuracy of preterm delivery in order to establish which uterine EMG recording location was optimal signal data. Overall, our results show a clear improvement in prediction accuracy of preterm delivery risk compared with previous approaches, achieving an impressive maximum AUC value of 0.986 when using signals from an electrode positioned below the navel. In sum, this provides a promising new method for analyzing uterine EMG signals to permit accurate clinical assessment of preterm delivery risk.

No MeSH data available.


Related in: MedlinePlus

p values of Student’s t test of the entropy ratios of the instantaneous amplitude of ith and jth component of IMFs of the uterine EMG signals.
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pone.0132116.g005: p values of Student’s t test of the entropy ratios of the instantaneous amplitude of ith and jth component of IMFs of the uterine EMG signals.

Mentions: Independent t tests were carried out on measures of Ramplitude and Rfrequency between all term (262 pregnant women) and preterm (38 pregnant women) subjects’ uterine EMG records. Fig 5 shows the p values of Student’s t test of the entropy ratios of the instantaneous amplitude of ith and jth component of IMFs of the uterine EMG signals. Fig 6 shows the p values for Student’s t test analysis of the entropy ratios of the instantaneous frequency of the ith and jth components of IMFs for the uterine EMG signals. It should be noted that the p values across the diagonal in Figs 5 and 6 were not considered in the analysis and so in Fig 5 the number of significant values(p<0.05) is 22 (out of 90), and in Fig 6 it is 21 (out of 90). All statistical tests were performed using SPSS software (version 17.0 SPSS Inc., Chicago, IL, USA).


Improved Prediction of Preterm Delivery Using Empirical Mode Decomposition Analysis of Uterine Electromyography Signals.

Ren P, Yao S, Li J, Valdes-Sosa PA, Kendrick KM - PLoS ONE (2015)

p values of Student’s t test of the entropy ratios of the instantaneous amplitude of ith and jth component of IMFs of the uterine EMG signals.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4498691&req=5

pone.0132116.g005: p values of Student’s t test of the entropy ratios of the instantaneous amplitude of ith and jth component of IMFs of the uterine EMG signals.
Mentions: Independent t tests were carried out on measures of Ramplitude and Rfrequency between all term (262 pregnant women) and preterm (38 pregnant women) subjects’ uterine EMG records. Fig 5 shows the p values of Student’s t test of the entropy ratios of the instantaneous amplitude of ith and jth component of IMFs of the uterine EMG signals. Fig 6 shows the p values for Student’s t test analysis of the entropy ratios of the instantaneous frequency of the ith and jth components of IMFs for the uterine EMG signals. It should be noted that the p values across the diagonal in Figs 5 and 6 were not considered in the analysis and so in Fig 5 the number of significant values(p<0.05) is 22 (out of 90), and in Fig 6 it is 21 (out of 90). All statistical tests were performed using SPSS software (version 17.0 SPSS Inc., Chicago, IL, USA).

Bottom Line: Next, the entropy values of both instantaneous amplitude and instantaneous frequency of the first ten IMF components are computed in order to derive ratios of these two distinct components as features.Discrimination accuracy of this approach compared to those proposed previously was then calculated using six differently representative classifiers.Overall, our results show a clear improvement in prediction accuracy of preterm delivery risk compared with previous approaches, achieving an impressive maximum AUC value of 0.986 when using signals from an electrode positioned below the navel.

View Article: PubMed Central - PubMed

Affiliation: Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Biomedicine, University of Electronic Science and Technology of China, Chengdu, China.

ABSTRACT
Preterm delivery increases the risk of infant mortality and morbidity, and therefore developing reliable methods for predicting its likelihood are of great importance. Previous work using uterine electromyography (EMG) recordings has shown that they may provide a promising and objective way for predicting risk of preterm delivery. However, to date attempts at utilizing computational approaches to achieve sufficient predictive confidence, in terms of area under the curve (AUC) values, have not achieved the high discrimination accuracy that a clinical application requires. In our study, we propose a new analytical approach for assessing the risk of preterm delivery using EMG recordings which firstly employs Empirical Mode Decomposition (EMD) to obtain their Intrinsic Mode Functions (IMF). Next, the entropy values of both instantaneous amplitude and instantaneous frequency of the first ten IMF components are computed in order to derive ratios of these two distinct components as features. Discrimination accuracy of this approach compared to those proposed previously was then calculated using six differently representative classifiers. Finally, three different electrode positions were analyzed for their prediction accuracy of preterm delivery in order to establish which uterine EMG recording location was optimal signal data. Overall, our results show a clear improvement in prediction accuracy of preterm delivery risk compared with previous approaches, achieving an impressive maximum AUC value of 0.986 when using signals from an electrode positioned below the navel. In sum, this provides a promising new method for analyzing uterine EMG signals to permit accurate clinical assessment of preterm delivery risk.

No MeSH data available.


Related in: MedlinePlus