Clinical trial NCT04235075: Computer-assisted Fetal Monitoring - Cardiology
Official title: Computer-assisted Fetal Monitoring - Cardiology
Study type: INTERVENTIONAL
Overall status: UNKNOWN
Phase: NA
Conditions: Pregnancy
Keywords: Signal Database
Pregnancy
Electrocardiogram
Usability
Multimodal signal acquisition
Lead sponsor: University Hospital, Grenoble
Sponsor class: OTHER
Collaborators: name: TIMC-IMAG
name: University Grenoble Alps
name: Clinical Investigation Centre for Innovative Technology Network
First posted: 2020-01-21
Enrollment: 20
Sex: FEMALE
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: NA
Intervention model: SINGLE_GROUP
Intervention model description: Creation of a multimodal database
Primary purpose: OTHER

Brief summary: In the context of fetal heart monitoring (prenatal and during childbirth), the SurFAO project offers an alternative to current clinical routines. The challenge is to extract, from non-invasive sensors on the maternal abdomen, a fetal electrocardiogram (ECGf) of great quality allowing a clinical diagnosis (follow-up of the FHR (Fetal Heart Rate)) and extraction of ECG waveforms).

The approach proposes a technological breakthrough shared by a consortium of researchers and clinicians. The originality is driven by innovative methodological choices: the use of a multimodal system (ECG coupling with PCG (phonocardiography)) for the signal acquisition in order to increase the robustness of information extraction, by taking into account clinical uses and the need to support the monitoring process, and by setting up a multimodal database.

The objective is to feed a database that will be used in the future to develop ECGf extraction methods.

Detailed description: To monitor the well-being of a fetus or for clinical diagnosis, the challenge is to extract a high-quality fetal electrocardiogram (fECG) signal from non-invasive sensors on the maternal abdomen.

As early as the 20th week of amenorrhea, heart rhythm disorders (tachycardia, bradycardia) can be detected in the fetus, most often by fortuitous circumstance, during routine obstetrical ultrasound examinations. It is then necessary to analyze these rhythmic anomalies, understand their origin and, if necessary, initiate pharmacotherapy. The effectiveness of the treatments is then monitored by ultrasound in the high-risk pregnancy department.

The analysis of a fetal electrocardiogram (fECG) provides information that allows to determine the nature of the rhythm disorder, its origin and therefore its potential severity.

The innovative methodological approach considered for the extraction of non-invasive ECGf is to combine 2 complementary modalities of the same cardiac phenomenon. This is achieved by combining the use of ECG sensors with sound sensors giving access to phonocardiographic signals (PCG).

Eligibility criteria: Inclusion Criteria:

* single pregnancy
* between 20 and 26 weeks of amenorrhea
* with a BMI between 18.5 and 30 at the beginning of pregnancy
* fetal heart considered normal after expert ultrasound
* examination conditions deemed correct by the expert
* registered in a social security scheme
* having signed the study consent form

Exclusion Criteria:

* subject to a legal protection measure or unable to express consent (guardianship, guardianship) (article L1121-8)
* deprived of liberty by judicial or administrative decision (article L1121-6)
* in a period of exclusion from another study
* with toxic consumption (i.e. tobacco, alcohol, cannabis)
* Intrauterine growth retardation (estimated fetal weight less than the 10th percentile)
* fetal heart rhythm disorders
* with unclear pregnancy term
* with pregnancy denial

Primary outcomes:
measure: ECG / PCG Signals database
timeFrame: 20 minutes
measure: Ultrasound signals database
timeFrame: 10 minutes
Secondary outcomes:
measure: Subject acceptability : Score
timeFrame: 10 minutes
measure: Subject Acceptability : Descriptive analysis
timeFrame: 10 minutes
measure: Use Error evaluation : System Usability Scale (SUS)
timeFrame: 10 minutes
measure: Use Error evaluation : Descriptive analysis
timeFrame: 60 minutes
Other outcomes:
Locations:
city: Grenoble
country: France
facility: University Hospital Grenoble Alpes
Study officials:
affiliation: University Hospital Grenoble Alpes
name: Matthias LACHUAD, MD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Noorzadeh S, Rivet B, Gumery PY. An application of Gaussian processes on ocular artifact removal from EEG. Annu Int Conf IEEE Eng Med Biol Soc. 2015 Aug;2015:554-7. doi: 10.1109/EMBC.2015.7318422.
citation: Noorzadeh S, Niknazar M, Rivet B, Fontecave-Jallon J, Gumery PY, Jutten C. Modeling quasi-periodic signals by a non-parametric model: application on fetal ECG extraction. Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:1889-92. doi: 10.1109/EMBC.2014.6943979.