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

NCT07573358 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 63

Last updated 2026-05-07

No results posted yet for this study

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

Interventions

OTHER

Sunnybrook Facial Grading System (FGS)

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

OTHER

AI-Based Facial Assessment

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

Sponsors & Collaborators

  • Cairo University

    lead OTHER

Principal Investigators

  • Ali Noureldin Hassanein, B.Sc. · Cairo University

Eligibility

Min Age
25 Years
Max Age
40 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-06-01
Primary Completion
2026-10-01
Completion
2026-12-01

Countries

  • Egypt

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 NCT07573358 on ClinicalTrials.gov