Clinical trial NCT03857126: Computer-assisted Fetal Monitoring - Obstetrics
Official title: Surveillance fœtale assistée Par Ordinateur - Obstétrique
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: ECG-PCG-CTG Acquisition on Pregnant Voluntary Subjects
Keywords: Signal Database
Pregnancy
Electrocardiogram
Phonocardiogram
Cardiotocography
Usability
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: 2019-02-27
Enrollment: 40
Sex: FEMALE
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: Pregnant women

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.

Eligibility criteria: 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.

Primary outcomes:
measure: ECG Signals Database
timeFrame: 30 minutes
measure: PCG Signals Database
timeFrame: 30 minutes
measure: CTG Signals Database
timeFrame: 30 minutes
Secondary outcomes:
measure: Subject Acceptability: Score
timeFrame: 15 minutes
measure: Subject Acceptability : Descriptive analysis
timeFrame: 15 minutes
measure: Use Error evaluation : System Usability Scale (SUS)
timeFrame: 15 minutes
measure: Use Error evaluation : Descriptive analysis
timeFrame: 15 minutes
Other outcomes:
Locations:
city: Grenoble
country: France
facility: University Hospital Grenoble
Study officials:
affiliation: CHU Grenoble Alpes
name: Véronique Equy
role: PRINCIPAL_INVESTIGATOR
References:
citation: Equy V, Buisson S, Heinen M, Schaal J-P, Hoffmann P, Sergent F. Confusion between maternal and fetal heart rate during delivery: risk factors and consequences British Journal of Midwifery, vol.20 (11), 2012
citation: Gobillot S, Fontecave-Jallon J, Equy V, Rivet B, Gumery PY, Hoffmann P. Non-invasive fetal monitoring using electrocardiography and phonocardiography: A preliminary study. J Gynecol Obstet Hum Reprod. 2018 Nov;47(9):455-459. doi: 10.1016/j.jogoh.2018.08.009. Epub 2018 Aug 23.
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.
citation: Noorzadeh S, Rivet B, Guméry PY. A multi-modal approach using a non-parametric model to extract fetal ECG. Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing (ICASSP), Brisbane, Australia, 2015, pp. 1856-60