Computer-assisted Fetal Monitoring - Cardiology

NCT ID: NCT04235075

Last Updated: 2020-09-23

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Clinical Phase

NA

Total Enrollment

20 participants

Study Classification

INTERVENTIONAL

Study Start Date

2020-08-31

Study Completion Date

2022-10-31

Brief Summary

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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

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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).

Conditions

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Pregnancy

Study Design

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Allocation Method

NA

Intervention Model

SINGLE_GROUP

Creation of a multimodal database
Primary Study Purpose

OTHER

Blinding Strategy

NONE

Study Groups

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Pregnancy volunteer subjects

Subjects who will agree to participate in the study will be pregnant women referred to the Grenoble Alpes University Hospital for expert fetal cardiac ultrasound examination who have not revealed any abnormalities.

Group Type EXPERIMENTAL

ECG/PCG and ultrasound signal acquisition

Intervention Type DEVICE

The ECG - PCG signals are acquired over a 20-minute monitoring phase with passive non invasive sensors (abdominal and thoracic). The volunteer's abdomen is photographed when the electrodes and sensors are installed. An ultrasonography is also performed for 10 minutes.

The session is filmed for 5 volunteers accepting the video. Any distinctive elements will be removed from photos and videos to prevent the identification of participants.

Interventions

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ECG/PCG and ultrasound signal acquisition

The ECG - PCG signals are acquired over a 20-minute monitoring phase with passive non invasive sensors (abdominal and thoracic). The volunteer's abdomen is photographed when the electrodes and sensors are installed. An ultrasonography is also performed for 10 minutes.

The session is filmed for 5 volunteers accepting the video. Any distinctive elements will be removed from photos and videos to prevent the identification of participants.

Intervention Type DEVICE

Eligibility Criteria

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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
Minimum Eligible Age

18 Years

Eligible Sex

FEMALE

Accepts Healthy Volunteers

Yes

Sponsors

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TIMC-IMAG

OTHER

Sponsor Role collaborator

University Grenoble Alps

OTHER

Sponsor Role collaborator

Clinical Investigation Centre for Innovative Technology Network

NETWORK

Sponsor Role collaborator

University Hospital, Grenoble

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Matthias LACHUAD, MD

Role: PRINCIPAL_INVESTIGATOR

University Hospital Grenoble Alpes

Locations

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University Hospital Grenoble Alpes

Grenoble, , France

Site Status RECRUITING

Countries

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France

Central Contacts

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Matthias LACHAUD, MD

Role: CONTACT

+33 4 76 76 94 95

Isabelle Boudry, PhD

Role: CONTACT

+33 4 76 76 66 45

Facility Contacts

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Matthias LACHAUD, MD

Role: primary

Isabelle Boudry, PhD

Role: backup

+33 4 76 76 66 45

References

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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.

Reference Type BACKGROUND
PMID: 26736322 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 25570347 (View on PubMed)

Related Links

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https://www.cic-it-grenoble.fr/projets/

Website of the Clinical Investigation Centre for Innovative Technology of the Grenoble Alpes University Hospital

Other Identifiers

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38RC19.309

Identifier Type: -

Identifier Source: org_study_id

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