The Editor's Feature emphasizes high-quality collections that have been developed in our journal each month. This Research Topic has been acknowledged by the Specialty Chief Editor of the Biosensors and Biomolecular Electronics section, Prof. Guozhen Liu for its outstanding contribution to the field, focus on a timely theme, and its team of excellent Topic Editors who are collaborating with us.
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Pregnancy and the complex events taking place in the mother-fetus system are characterized by a peculiar trait: fast and continuous evolution in time. The fetus passes from two cells to three kilograms in about nine months and the mother body must rapidly adapt. Given the above-described time-evolving and complex system, a single snapshot during pregnancy (usually consisting of an echography and a CTG recording) is not enough. If remedies for acute and life-threatening scenarios are somehow part of clinical practice, little is known on the long-term influence of other risk factors, less severe but arising in time. These factors may be the cause of long-term pathologies with influence on future wellbeing for both mother and newborns.
Striking examples of minor alterations are those associated with incorrect dietary habits. Disequilibrium in the glucose metabolism, induced by pregnancy, is likely to result in mothers developing gestational diabetes. Late diagnosis of preeclampsia can lead to severe intervention during delivery increasing risk of premature birth and cesarean section probability. The main goal of this Research Topic is to collect state-of-the-art technologies and methods for implementing a novel antenatal monitoring system for a reliable checkup of maternal and fetal conditions throughout pregnancy.
It will be based on the integration of wearable sensors and devices connected with an ad-hoc smartphone application in communication with a remote obstetrical clinical center. Advanced signal and image processing tools should be proposed for extracting information from fetal heart rate, uterine contractions, continuous glucose sensors, and US images captured by a portable probe with a particular focus on multivariate analysis, machine learning techniques, and image analysis by deep learning.
Based on the growing literature providing evidence on the fact that the mother-fetus system should be considered as a whole, in this proposal pregnancy is conceptualized as a continuously evolving system that needs to be investigated by means of time-varying approaches. The crucial expected outcome is the integration of the established clinical knowledge with the most advanced technologies and the results of computational analysis. Such multilevel integration is expected to provide reliable and translatable clinical guidelines towards pregnancy management encompassing a more inclusive monitoring framework designed on a patient-specific level.
Authors are requested to submit Original Research and Review manuscripts regarding technologies and methodologies applied to antenatal monitoring for fetal well-being assessment and fetal risks identification, with particular focus on :
· Wearable fetal monitoring systems (fECG, CTG, Echography, others,…)
· Fetal Heart Rate and uterine contractions analysis (non-linear methods)
· New sensors and/or devices for fetal well-being assessment
· Machine learning techniques to identify early pathological conditions in fetal signal
· Echographic image analysis and measurements
· Deep learning methods applied to signals and images for assessing fetal wellbeing
The Editor's Feature emphasizes high-quality collections that have been developed in our journal each month. This Research Topic has been acknowledged by the Specialty Chief Editor of the Biosensors and Biomolecular Electronics section, Prof. Guozhen Liu for its outstanding contribution to the field, focus on a timely theme, and its team of excellent Topic Editors who are collaborating with us.
*******************************************************************
Pregnancy and the complex events taking place in the mother-fetus system are characterized by a peculiar trait: fast and continuous evolution in time. The fetus passes from two cells to three kilograms in about nine months and the mother body must rapidly adapt. Given the above-described time-evolving and complex system, a single snapshot during pregnancy (usually consisting of an echography and a CTG recording) is not enough. If remedies for acute and life-threatening scenarios are somehow part of clinical practice, little is known on the long-term influence of other risk factors, less severe but arising in time. These factors may be the cause of long-term pathologies with influence on future wellbeing for both mother and newborns.
Striking examples of minor alterations are those associated with incorrect dietary habits. Disequilibrium in the glucose metabolism, induced by pregnancy, is likely to result in mothers developing gestational diabetes. Late diagnosis of preeclampsia can lead to severe intervention during delivery increasing risk of premature birth and cesarean section probability. The main goal of this Research Topic is to collect state-of-the-art technologies and methods for implementing a novel antenatal monitoring system for a reliable checkup of maternal and fetal conditions throughout pregnancy.
It will be based on the integration of wearable sensors and devices connected with an ad-hoc smartphone application in communication with a remote obstetrical clinical center. Advanced signal and image processing tools should be proposed for extracting information from fetal heart rate, uterine contractions, continuous glucose sensors, and US images captured by a portable probe with a particular focus on multivariate analysis, machine learning techniques, and image analysis by deep learning.
Based on the growing literature providing evidence on the fact that the mother-fetus system should be considered as a whole, in this proposal pregnancy is conceptualized as a continuously evolving system that needs to be investigated by means of time-varying approaches. The crucial expected outcome is the integration of the established clinical knowledge with the most advanced technologies and the results of computational analysis. Such multilevel integration is expected to provide reliable and translatable clinical guidelines towards pregnancy management encompassing a more inclusive monitoring framework designed on a patient-specific level.
Authors are requested to submit Original Research and Review manuscripts regarding technologies and methodologies applied to antenatal monitoring for fetal well-being assessment and fetal risks identification, with particular focus on :
· Wearable fetal monitoring systems (fECG, CTG, Echography, others,…)
· Fetal Heart Rate and uterine contractions analysis (non-linear methods)
· New sensors and/or devices for fetal well-being assessment
· Machine learning techniques to identify early pathological conditions in fetal signal
· Echographic image analysis and measurements
· Deep learning methods applied to signals and images for assessing fetal wellbeing