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Computerized Facial Recognition for Automated Diagnosis of the Facio-Scapulo-Humeral Muscular Dystrophy (FSMHD)

NCT04377217 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 17

Last updated 2023-11-15

No results posted yet for this study

Summary

The clinical diagnosis of Facio-Scapulo-Humeral Muscular Dystrophy (FSHMD) requires the movement of patients to a medical centre and a lengthy examination involving medical personnel, and may be underestimated in the most moderate cases. Thus, it requires costly and burdensome logistics both for patients living in remote areas and having to undertake long and expensive travel, and for clinical staff. This is an obstacle to large-scale diagnosis. The investigators plan to alleviate these limitations through the use of digital facial analysis technology that would enable large-scale diagnosis of patients through telemedicine.

Motivated by the reasons described above and by preliminary results, the goal of this project is to develop methods to automatically detect and monitor the progression of this disease using computer vision algorithms. In order to do this, the investigators will first build up a bank of images and videos of patients with moderate to severe FSHMD, patients with other muscular dystrophies causing facial muscle asymmetry, as well as control subjects without facial involvement. Each of these subjects will be characterized clinically and genetically.

The investigators will then develop computer tools using video and audio sensors capable of detecting facial muscle damage in patients with FSHMD and differentiating them from control subjects on the one hand and patients with other muscular dystrophies on the other hand. The investigators wish to use the most recent advances in terms of "deep-learning" and improve their architecture in order to achieve our objectives.

In addition to this holistic approach, the investigators will study facial recognition approaches capable of accurately identifying different facial areas on images, as well as the relevance of different statistical properties of facial dynamics (duration and intensity). These algorithms will also be useful for monitoring the evolution of facial damage in order to develop a specific measurement tool that could be used in patient follow-up and in clinical trials on early stages of the disease.

Conditions

  • Facio-Scapulo-Humeral Dystrophy

Interventions

OTHER

Video recording

The experimenter will make a standardized video of the patient during the inclusion process, and a second one after 18 months, in order to evaluate the evolution of facial damage. Then algorithms will be developped to be able of differentiating FSHMD patients with facial damage from control subjects using video and audio recordings.

Sponsors & Collaborators

  • Centre Hospitalier Universitaire de Nice

    lead OTHER

Principal Investigators

  • Luisa VILLA, Dr · Centre Hospitalier Universitaire de Nice

Study Design

Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Model
SINGLE_GROUP

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2019-03-05
Primary Completion
2019-07-25
Completion
2019-07-25

Countries

  • France

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04377217 on ClinicalTrials.gov