Classification of fetal compromise during labour: signal processing and feature engineering of the cardiotocograph

@article{oSullivan2021ClassificationOF,
  title={Classification of fetal compromise during labour: signal processing and feature engineering of the cardiotocograph},
  author={Matt o'Sullivan and Tatiana Gabruseva and Gráinne M. Boylan and Mairead O'Riordan and Gordon Lightbody and William G. Marnane},
  journal={2021 29th European Signal Processing Conference (EUSIPCO)},
  year={2021},
  pages={1331-1335}
}
Cardiotocography (CTG) is the main tool used for fetal monitoring during labour. Interpretation of CTG requires dynamic pattern recognition in real time. It is recognised as a difficult task with high inter- and intra-observer disagreement. Machine learning has provided a viable path towards objective and reliable CTG assessment. In this study, novel CTG features are developed based on clinical expertise and system control theory using an autoregressive moving-average (ARMA) model to… 

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References

SHOWING 1-10 OF 21 REFERENCES

Investigating pH based evaluation of fetal heart rate (FHR) recordings

TLDR
An approach to Fetal Heart Rate (FHR) classification using pH is presented that could serve as a benchmark for reporting results on the unique open-access CTU-UHB CTG database, the largest and the only freely available database of this kind.

Classification of Normal and Hypoxic Fetuses From Systems Modeling of Intrapartum Cardiotocography

TLDR
The utility of this modeled signal pair as an input-output system using a system identification approach and a detector that combined the decisions of classifiers using both feature sets for early detection of cases needing clinical intervention is demonstrated.

Continuous cardiotocography during labour: Analysis, classification and management.

Sparse Support Vector Machine for Intrapartum Fetal Heart Rate Classification

TLDR
Intrapartum fetal acidosis detection is improved in several respects: an original multivariate classification targeting both sparse feature selection and high performance is devised; state-of-the-art performance is obtained on a much larger database than that generally studied with description of common pitfalls in supervised classification performance assessments.

Automatic Evaluation of FHR Recordings from CTU-UHB CTG Database

TLDR
For this paper, new CTU-UHB CTG database was used to compute more than 50 features, ranging from classical morphological features based on FIGO guidelines to frequency-domain and non-linear features.

Intrapartum Fetal Heart Rate Classification: Cross-Database Evaluation

TLDR
This work relies on the the use of two independent databases in order to asses relevantly acidosis detection performance and to address important issues of knowledge transfer ( features, classification model) from one database to the other.

Multimodal Convolutional Neural Networks to Detect Fetal Compromise During Labor and Delivery

TLDR
It is suggested that the most promising way forward are hybrid approaches to CTG interpretation in labor, in which different diagnostic models can estimate the risk for different types of fetal compromise, incorporating clinical knowledge with data-driven analyses.

Phase‐rectified signal averaging for intrapartum electronic fetal heart rate monitoring is related to acidaemia at birth

TLDR
It is determined whether PRSA relates to acidaemia in labour, and its performance to short‐term variation (STV), a related computerised FHR feature, is compared.

Open access intrapartum CTG database

TLDR
A new open-access CTG database is introduced which should give the research community common ground for comparison of results on reasonably large database and it is anticipated that after reading the paper the reader will understand the context of the field from clinical and technical perspectives which will enable him/her to use the database and also understand its limitations.

Computerized data‐driven interpretation of the intrapartum cardiotocogram: a cohort study

TLDR
It is hypothesized that OxSys can outperform clinical diagnosis of “fetal distress”, when optimized and tested over large retrospective data sets.