Surveillance fœtale assistée Par Ordinateur - Obstétrique

Computer-assisted Fetal Monitoring - Obstetrics


Lead sponsor: University Hospital, Grenoble

Collaborator: TIMC-IMAG
University Grenoble Alps
Clinical Investigation Centre for Innovative Technology Network

Source University Hospital, Grenoble
Brief Summary

In the context of fetal heart monitoring, the SurFAO project offers an alternative to current clinical routines. The challenge is to extract, from few 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 proposed 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 (phonocardiographic)) for the signal acquisition in order to increase the robustness of information extraction, by taking into account clinical uses and the need for the monitoring process support, and by setting up a reference for this multimodal database.

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

Detailed Description

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

During childbirth, fetal monitoring is assessed by the fetal heart rate (FHR), classically from cardiotocography (CTG). The aim is to monitor FHR variability anomalies that reflect a too high fetal malaise. It is very common to have difficulties to reliably record FHR due to confusion of rhythms of the mother and the fetus that can lead to unnecessary caesareans. With 800000 childbirths in France per year, improving the reliability of FHR estimation by fECG analysis is therefore of high clinicalinterest.

To deal with, the proposed approach aims at coupling two complementary cardiac information acquired at the best-located position. Therefore, the proposed solution is (i) to combine the use of electrophysiological sensors ECG and acoustic sensors of microphonic type that can register phonocardiographic signals (PCG), (ii) to assist by computer the clinical expertise to choose the best sensors location. Several methodological aspects will be considered: to improve the robustness of the FHR estimation with degraded signals based on multimodality, to overcome some practical limitations to extract the fECG waveforms by enhancing the process extraction with PCG and to assist the user in the sensors choice and placement by predicting their best locations and their kinds (ECG or PCG).

The SurFAO project proposes then an original approach of computer-assisted fetal monitoring and thus differs from previous published works of fECG extraction solutions, only based on algorithmic performances mostly in well-controlled situations. The original aspects of the investigator's proposal are the innovative methodological choices based on multimodality and informed recording process, the consideration of the medical uses and of the necessity to help the clinical monitoring to design the algorithms, the new reference multimodal database, and the academic-clinical consortium, that will guarantee the relevance of all proposed parts.

Overall Status Recruiting
Start Date May 2, 2019
Completion Date September 2020
Primary Completion Date September 2020
Study Type Observational
Primary Outcome
Measure Time Frame
ECG Signals Database 30 minutes
PCG Signals Database 30 minutes
CTG Signals Database 30 minutes
Secondary Outcome
Measure Time Frame
Subject Acceptability: Score 15 minutes
Subject Acceptability : Descriptive analysis 15 minutes
Use Error evaluation : System Usability Scale (SUS) 15 minutes
Use Error evaluation : Descriptive analysis 15 minutes
Enrollment 40

Intervention type: Other

Intervention name: Signal acquisition

Description: ECG-PCG-CTG synchronized signals acquisition over a monitoring phase of 30 minutes. These signals will be acquired with passive non invasive sensors (abdominal and thoracic).

Arm group label: Pregnancy volunteer subjects

Other name: Non invasive ECG-PCG-CTG sensors


Sampling method: Probability Sample


Inclusion Criteria:

- Pregnant of a single pregnancy,

- Aged over 18,

- During the 9th month of pregnancy (> 37 weeks),

- With uncomplicated maternal and fetal pregnancy follow-up,

- With a BMI between 18.5 and 30 at the beginning of pregnancy,

- Without a notable medical history,

- Enrolled in a social security scheme,

- Having signed the consent form for the study.

Exclusion Criteria:

- Subject under guardianship, protected by law or deprived of liberty (Article L1121-8),

- Subject under administrative or judicial supervision,

- Subject in exclusion period of another study,

- With toxic consumption (i.e. tobacco, alcohol, cannabis),

- With inaccurate pregnancy term,

- With denial of pregnancy.

Gender: Female

Gender based: Yes

Gender description: Pregnant women

Minimum age: 18 Years

Maximum age: N/A

Healthy volunteers: Accepts Healthy Volunteers

Overall Official
Last Name Role Affiliation
Véronique Equy Principal Investigator CHU Grenoble Alpes
Overall Contact

Last name: Julie Fontecave-Jallon

Phone: +33456520063

Email: [email protected]

facility status contact University Hospital Grenoble Véronique Equy, MD
Location Countries


Verification Date

March 2020

Responsible Party

Responsible party type: Sponsor

Has Expanded Access No
Arm Group

Arm group label: Pregnancy volunteer subjects

Description: Subjects who will agree to participate in the investigator's study will be pregnant healthy subjects with no particular antecedent, followed at the University Hospital of Grenoble for a physiological pregnancy; their child will be not affected by any prenatal pathology. Subjects will be enrolled in a 30 min monitoring phase to collect signals from ECG-PCG-CTG abdominal and thoracic non invasive sensors.

Acronym SURFAO-Obst
Patient Data No
Study Design Info

Observational model: Cohort

Time perspective: Prospective