A Novel Large Structured Cardiotocographic Database

In this work we present the creation of a large, structured database of CardioTocoGraphic (CTG) recordings, starting from a raw dataset containing tracings collected between 2013 and 2021 by the medical team of the University Hospital Federico II of Naples. The aim of the work is to provide a big, structured database of real clinical cardiotocographic data, useful for subsequent processing and analysis through state-of-the-art methods, in particular Deep Learning Methods. This organized dataset could lead to an increase of the diagnostic accuracy of CTG analysis in the discrimination of healthy and unhealthy fetuses.

[1]  W. P. Marnane,et al.  Challenges of Developing Robust AI for Intrapartum Fetal Heart Rate Monitoring , 2021, Frontiers in Artificial Intelligence.

[2]  Mohammad Saber Iraji,et al.  Prediction of fetal state from the cardiotocogram recordings using neural network models , 2019, Artif. Intell. Medicine.

[3]  J. Bernardes,et al.  Twenty‐five years after the FIGO guidelines for the use of fetal monitoring: Time for a simplified approach? , 2010, International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics.

[4]  Everett F. Magann,et al.  Intrapartum nonreassuring fetal heart rate tracing and prediction of adverse outcomes: interobserver variability. , 2008, American journal of obstetrics and gynecology.

[5]  Xiaotian Li,et al.  Approximate entropy of fetal heart rate variability as a predictor of fetal distress in women at term pregnancy , 2005, Acta obstetricia et gynecologica Scandinavica.

[6]  Sergio Cerutti,et al.  Linear and nonlinear parameters for the analysisof fetal heart rate signal from cardiotocographic recordings , 2003, IEEE Transactions on Biomedical Engineering.

[7]  D. Ayres-de- Campos,et al.  SisPorto 2.0: a program for automated analysis of cardiotocograms. , 2000, The Journal of maternal-fetal medicine.

[8]  Jeffrey M. Hausdorff,et al.  Physionet: Components of a New Research Resource for Complex Physiologic Signals". Circu-lation Vol , 2000 .

[9]  S. Pincus.  Approximate entropy (ApEn) as a complexity measure. , 1995, Chaos.

[10]  Giovanni Magenes,et al.  2CTG2: A new system for the antepartum analysis of fetal heart rate , 2007 .

[11]  Sandra Hernandez,et al.  Visual analysis of antepartum fetal heart rate tracings: inter- and intra-observer agreement and impact of knowledge of neonatal outcome , 2005, Journal of perinatal medicine.

[12]  L. Devoe.  Computerized analysis of fetal heart rate , 1990 .