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An objective, markerless videosystem for staging facial palsy
Summary
This study introduces an objective video analysis for unilateral peripheral facial palsy (UPFP). The method uses mathematical algorithms to quantify facial asymmetry, offering a reliable alternative to subjective assessments.
Area of Science:
- Medical Imaging
- Biomedical Engineering
- Neurology
Background:
- Unilateral peripheral facial palsy (UPFP) diagnosis often relies on subjective clinical assessments.
- Objective and quantifiable methods are needed for accurate UPFP classification and monitoring.
Purpose of the Study:
- To introduce a novel, objective video recording method for classifying UPFP.
- To develop a markerless software-based approach using mathematical algorithms for facial nerve impairment detection.
Main Methods:
- Video recording of UPFP patients (House-Brackmann grades II-V) during forehead frowning and smiling.
- Utilizing software to identify facial points as numerical data.
- Calculating asymmetry index based on facial point shifts between healthy and affected sides.
Main Results:
- Specific asymmetry index ranges were identified for each House-Brackmann grade.
- Positive correlation observed between shift differences and asymmetry index.
- Negative correlation found between asymmetry indexes and HB grade.
Conclusions:
- The objective system successfully identified numerical ranges of facial asymmetry.
- These ranges correlate with outcomes from current subjective assessment methods.
- This markerless system provides a consistent and objective tool for UPFP evaluation.
Keywords:
Facial palsyMachine learningObjective grading systemSmartphoneSubjective grading systemVideorecording
