Reliability of Bi- dimensional System of facial movement analysis in patients with Peripheral facial palsy.
Year: 2024
Type: article
Abstract: BACKGROUND -Peripheral facial palsy (PFP) is a condition that substantially alters facial function and has a noticeable impact on appearance. Precise evaluation of the level of functioning is required for objectivity in diagnosis of facial function and monitoring clinical changes while planning and evaluating therapeutic interventions for patients with PFP. OBJECTIVE – The present study was conducted with an objective to find out the reliability and internal consistency of the Kinovea software based bi-dimensional tool in objectively evaluating Peripheral facial palsy. METHODS- 40 Patients who were diagnosed with peripheral Facial palsy were categorized on stage of House Brackmann facial nerve grading scale. Landmarks were placed on face and image was captured in resting facial symmetry and video recording of different facial expressions like closing of eye, raising of eyebrows and smiling was performed by two different examiners. The data was processed by Kinovea software to measure different facial angles. RESULTS -The intra-rater reliability (re-test reliability) for the measurement of the facial angles using Kinovea software at rest and movement analysis on both the affected and nonaffected sides was excellent (Rest-ICC-0.94, α>0.95)(Movement- ICC-0.92, α>0.98).The reliability between raters on analysis at rest and movement in both the affected and non-affected side were also excellent (Rest-ICC->0.96, α>0.96), (Movement-ICC>0.86, α>0.87). CONCLUSION -Two-dimensional motion analysis system using Kinovea software can be considered as a reliable method for the assessment of unilateral Peripheral Facial Palsy and can be used extensively to detect deviation in facial angles in resting and movement.
DOI: 10.37506/y5s21051
Institution: Shri Dharmasthala Manjunatheshwara University
Language: English
Subfield: Neurology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4405334905