Development and Application of a Dynamic Three-dimensional Quantitative Facial Measurement Device
1 other identifier
observational
200
1 country
1
Brief Summary
The aim of this project is to successfully develop and industrialise the "Facial Movement 3D Dynamic Quantitative Measurement Device", which is a commercial device that can provide dynamic indicators of facial movement, and can practically solve the evaluation problems of facial paralysis for doctors and patients, and has important clinical value and social benefits.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Jul 2022
Typical duration for all trials
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
July 1, 2022
CompletedFirst Submitted
Initial submission to the registry
July 27, 2023
CompletedFirst Posted
Study publicly available on registry
August 8, 2023
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 30, 2024
CompletedStudy Completion
Last participant's last visit for all outcomes
December 30, 2024
CompletedAugust 8, 2023
August 1, 2023
2.5 years
July 27, 2023
August 7, 2023
Conditions
Outcome Measures
Primary Outcomes (2)
Facial feature point displacement distance
Displacement of corresponding facial feature points when volunteers perform specific actions such as specific expressions (raising eyebrow, closing eyes, shrugging nose, smiling and whistling)
3 months
Facial Feature Point Velocity
Velocity of the corresponding facial feature points of volunteers when accomplishing specific actions such as specific expressions (raising eyebrows, closing eyes, shrugging nose, smiling, whistling)
3 months
Study Arms (2)
training session
A total of 150 facial expression videos of healthy volunteers and facial palsy patients were collected as a training set for the algorithm
test set
A total of 50 cases of healthy volunteers and patients with facial palsy were used as the test set for the algorithm
Interventions
Eligibility Criteria
Based on previous face data collection often use larger public datasets, such as the AFLW dataset with 20,000 images. we need the same order of magnitude of local ethnographic data for migration learning. At the same time, the data in the dataset is improved according to the need to improve the accuracy of the labelled data at key points. Take about 100 effective frames for each data set. Need to complete about 200 people of various types of face data acquisition. The test group data is generally designed to be more than 20% of the training data, so the number of test group samples is designed to be 50 groups.
You may qualify if:
- Older than 14 years
- No history of facial surgery, facial trauma, or scars obscuring the facial features.
- Able to perform relevant actions according to instructions
- Willingness to participate in the study
You may not qualify if:
- Unwillingness to participate in the study
- Unable to co-operate with relevant command actions
- Obvious trauma, scars, etc. obscuring the facial features
- Less than 14 years of age
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Peking Union Medical College Hospital
Beijing, Beijing Municipality, 100730, China
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Guodong Feng
Peking Union Medical College Hospital
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- chief physician
Study Record Dates
First Submitted
July 27, 2023
First Posted
August 8, 2023
Study Start
July 1, 2022
Primary Completion
December 30, 2024
Study Completion
December 30, 2024
Last Updated
August 8, 2023
Record last verified: 2023-08
Data Sharing
- IPD Sharing
- Will not share