Validation of Artificial Intelligence-Based Facial Paralysis Assessment in Patients With Bell's Palsy (AI-FACE)
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Participants with unilateral Bell's palsy will be recruited for a single assessment session. The assessment involves two primary components:
Clinical Assessment: A qualified physical therapist will grade the patient's facial function using the Sunnybrook Facial Grading System, which evaluates resting symmetry, degree of voluntary movement, and synkinesis.
AI Assessment: A computer-vision-based system will utilize a standard camera to detect 468 facial landmarks in real-time. The system calculates a composite asymmetry score by comparing the movement amplitude and positioning of the affected side of the face against the healthy side during standardized facial expressions.
The study will utilize Spearman's rank correlation coefficient to analyze the relationship between the AI-derived scores and the Sunnybrook scores to establish concurrent validity. No personal images or videos will be stored; the AI performs real-time processing and immediate data deletion to ensure participant privacy.
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: Ali Noureldin Hassanein, B.Sc., PT.
- Phone Number: +201142154162
- Email: alionour22@gmail.com
Study Locations
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Giza Governorate
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Giza, Giza Governorate, Egypt, 12613
- faculty of physical therapy, Cairo university
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Contact:
- Ali Noureldin Hassanein, B.Sc.
- Phone Number: 01142154162
- Email: alionour22@gmail.com
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Principal Investigator:
- Ali Noureldin Hassanein, B.Sc.
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Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- Patients with unilateral Bell's palsy.
- Patients must be within one month of onset of Bell's palsy symptoms at the time of enrollment.
- Body mass index (BMI) less than 30 $kg/m^2$.
- Patients must be cooperative and able to follow simple verbal instructions during facial movement tasks.
Exclusion Criteria:
- Bilateral facial paralysis or recurrent Bell's palsy.
- Facial nerve palsy due to known secondary causes (e.g., trauma, neoplasm, infection, stroke, Ramsay Hunt syndrome, or otitis media).
- Facial deformities, scars, or burns that interfere with facial motion detection.
- Uncooperative or cognitively impaired individuals unable to follow instructions or maintain required facial postures.
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
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Patients with Unilateral Bell's Palsy
Sixty-three patients of both sexes, aged 25-40 years, with a body mass index (BMI) less than 30 $kg/m^2$.
Participants must be within one month of the onset of Bell's palsy symptoms and be able to follow verbal instructions during facial movement tasks.
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Clinical grading of facial muscle paralysis based on resting symmetry, symmetry of voluntary movements, and synkinesis detection.
Real-time computer vision analysis using deep-learning-based landmark detection to track 468 facial points during standardized facial expressions.
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Spearman's Rank Correlation Coefficient between AI-derived scores and Sunnybrook Facial Grading System scores.
Time Frame: Baseline (single assessment at the time of enrollment).
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This measure evaluates the concurrent validity of the AI-based assessment system.
The AI system uses 468 facial landmarks to calculate a composite asymmetry score (0-100%).
These results will be correlated with the clinical scores from the Sunnybrook Facial Grading System (0-100), where higher scores indicate better facial function.
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Baseline (single assessment at the time of enrollment).
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Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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AI-Based Composite Asymmetry Score.
Time Frame: Baseline.
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The specific numerical output generated by the computer-vision system.
It quantifies facial symmetry by measuring the amplitude of movement (in pixels/displacement) during five standardized facial expressions: brow lift, eye closure, broad smile, snarl, and lip pucker.
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Baseline.
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Collaborators and Investigators
Sponsor
Sponsor
Investigators
Investigators
- Principal Investigator: Ali Noureldin Hassanein, B.Sc., Cairo University
Study record dates
Study Major Dates
Study Start (Estimated)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- P.T.REC/012/006311
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
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