An interventional study of Maternal and fetal electrocardiograms separation in Pregnancy Related, sponsored by I.M. Sechenov First Moscow State Medical University. Recruiting at 1 site in Russia. Open to female participants aged 18 Years to 55 Years. Per ClinicalTrials.gov, last updated 2026-04-08.
Sponsored by I.M. Sechenov First Moscow State Medical University · Not applicable, Interventional, and Other
Effective monitoring of fetal heart activity during the second and third trimesters remains a vital challenge in perinatal medicine. This study proposes an adaptive algorithm for extracting the fetal electrocardiograms signal from abdominal ECG in pregnant women, considering the physiological characteristics of each trimester. Utilizing modern machine learning methods, independent component analysis, and data from wearable textile electrodes. The goal is to enhance the accuracy and reliability of automatic signal separation. A dataset of 300 recordings will be collected and analyzed. The resulting algorithm will enable rapid and precise detection of fetal heartbeats. To validate the algorithm, 50 patients will be recruited separately.
Research Objective Development and validation of an algorithm for separating maternal and fetal electrocardiographic signals based on non-invasive abdominal ECG in pregnant women during the second and third trimesters of gestation.
Research Tasks
I.M. Sechenov First Moscow State Medical University is the lead sponsor of 137 studies on the registry; 28 are open to participants now.
Counted across the registry records on this site, refreshed daily.
Inclusion Criteria:
Exclusion Criteria:
Exclusion criteria:
1. Patient's refusal to continue participation in the study.
Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Informed consent
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Pregnant women in the 2nd to 3rd trimester.
Other: Maternal and fetal electrocardiograms separation
Sensors are attached to the pregnant woman's abdomen on pre-prepared sites, and data are recorded for at least 10 minutes. Afterwards, the ECG signals are processed to remove noise.
Correlation coefficient between automatically extracted fetal heart rates and reference. signals
Сardiotocography (CTG) will be used as a reference.
Time frame: Through study completion, an average of 1 year
Signal processing time and computational complexity of the algorithm.
The signal processing time refers to the duration required for the algorithm to analyze and process the input signals, including steps such as filtering, noise removal, feature extraction, and data alignment.
Time frame: Through study completion, an average of 1 year
Accuracy of R-peak detection: number of correctly identified fetal heartbeats (sensitivity) and number of false positives (specificity).
The accuracy of R-peak detection refers to the algorithm's ability to correctly identify fetal heartbeats within the recorded signals. Sensitivity (true positive rate) indicates the proportion of actual fetal heartbeats that were correctly detected by the algorithm. Specificity (true negative rate or false positive rate) reflects the number of false detections, i.e., instances where non-heartbeat signals were incorrectly identified as fetal heartbeats. High sensitivity and specificity are essential for reliable fetal heart rate monitoring, minimizing missed beats and false alarms.
Time frame: Through study completion, an average of 1 year
Proportion of rejected or invalid segments where the algorithm failed to reliably extract fetal data.
The proportion of rejected or invalid segments refers to the percentage of data segments in which the algorithm was unable to reliably extract fetal heart rate information. These segments are typically excluded from analysis due to poor signal quality, noise, or other artifacts that prevent accurate detection of fetal data.
Time frame: Through study completion, an average of 1 year
Plan to share: No
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