Validation of Artificial Intelligence-Based Facial Paralysis Assessment in Patients With Bell's Palsy

NCT07573358 | Not Yet Recruiting

• 1 other identifier: P.T.REC/012/006311
• Study Type: observational
• Target: 63
• Locations: 1 country
• Sites: 1

Brief Summary

This observational study aims to assess the concurrent validity of an artificial intelligence (AI)-based facial paralysis assessment system in patients with unilateral Bell's palsy. Currently, clinical assessment relies on subjective scales like the Sunnybrook Facial Grading System, which can vary between different observers. This study will compare AI-generated composite asymmetry scores-derived from real-time computer vision analysis of facial landmarks-with scores from the Sunnybrook system. The goal is to determine if AI can provide a valid, objective method for monitoring facial nerve recovery.

Conditions

Bell's Palsy; Facial Nerve Paralysis

Keywords

Facial Asymmetry; Artificial Intelligence; Sunnybrook Facial Grading System; Computer Vision

Outcome Measures

Primary Outcomes (1)

• Spearman's Rank Correlation Coefficient between AI-derived scores and Sunnybrook Facial Grading System scores.

  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.

  Baseline (single assessment at the time of enrollment).

Secondary Outcomes (1)

• AI-Based Composite Asymmetry Score.

  Baseline.

Study Arms (1)

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.

Other: Sunnybrook Facial Grading System (FGS); Other: AI-Based Facial Assessment

Interventions

Sunnybrook Facial Grading System (FGS) OTHER

Clinical grading of facial muscle paralysis based on resting symmetry, symmetry of voluntary movements, and synkinesis detection.

Patients with Unilateral Bell's Palsy

AI-Based Facial Assessment OTHER

Real-time computer vision analysis using deep-learning-based landmark detection to track 468 facial points during standardized facial expressions.

Patients with Unilateral Bell's Palsy

Eligibility Criteria

• Age: 25 Years - 40 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64)
• Sampling Method: Non-Probability Sample

Study Population

Sixty-three patients of both sexes with unilateral Bell's palsy will be recruited from private clinics. Patients will be diagnosed by a neurologist based on clinical examination.

You may qualify if:

• 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.

You may not qualify if:

• 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.

Sponsors & Collaborators

• Cairo University: lead

Study Sites (1)

Faculty of Physical Therapy, Cairo University

Giza, Giza Governorate, 12613, Egypt

Location

MeSH Terms

Conditions

Bell Palsy; Facial Asymmetry

Condition Hierarchy (Ancestors)

Herpesviridae Infections; DNA Virus Infections; Virus Diseases; Infections; Mouth Diseases; Stomatognathic Diseases; Facial Nerve Diseases; Cranial Nerve Diseases; Nervous System Diseases; Pathological Conditions, Anatomical; Pathological Conditions, Signs and Symptoms

Study Officials

• Ali Noureldin Hassanein, B.Sc.

  Cairo University

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Ali Noureldin Hassanein, B.Sc., PT.

CONTACT

+201142154162; alionour22@gmail.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: CROSS SECTIONAL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Master's Degree Candidate, Faculty of Physical Therapy, Cairo University

Study Record Dates

• First Submitted: May 1, 2026
• First Posted: May 7, 2026
• Study Start (Estimated): June 1, 2026
• Primary Completion (Estimated): October 1, 2026
• Study Completion (Estimated): December 1, 2026
• Last Updated: May 7, 2026

Record last verified: 2026-05

Data Sharing

• IPD Sharing: Will not share

Locations

EG (1)