Actively Recruiting
Maternal and Fetal Electrocardiograms Separation Algorithm
Led by I.M. Sechenov First Moscow State Medical University · Updated on 2026-04-08
350
Participants Needed
1
Research Sites
119 weeks
Total Duration
On this page
AI-Summary
What this Trial Is About
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.
CONDITIONS
Official Title
Maternal and Fetal Electrocardiograms Separation Algorithm
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Age over 18 years
- Recordings obtained during the second or third trimester of pregnancy
- Recording duration of at least 5 minutes
- Singleton pregnancy
- Signed informed consent
You will not qualify if you...
- Age under 18 years
- Multiple pregnancy
- Recent medical procedures or interventions that could affect the quality of electrocardiographic data
- Severe maternal conditions such as severe eclampsia, shock, or severe organ failure
- Severe fetal conditions such as significant hypoxia, severe placental-fetal syndrome, or other life-threatening states
- Patient's refusal to continue participation in the study
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Trial Site Locations
Total: 1 location
1
V.F. Snegirev Clinic of Obstetrics and Gynecology of I.M. Sechenov First Moscow State Medical University
Moscow, Russia, 119435
Actively Recruiting
Research Team
P
Philipp Yu Kopylov, Prof.
CONTACT
S
Sheron R Rakhamimova, PhD Student
CONTACT
How is the study designed?
Study Type
INTERVENTIONAL
Masking
NONE
Allocation
NA
Model
SINGLE_GROUP
Primary Purpose
OTHER
Number of Arms
1
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