Quantified analysis of facial movement: A reference for clinical applications
Most techniques for evaluating unilateral impairments in facial movement yield subjective measurements. The objective of the present study was to define a reference dataset and develop a visualization tool for clinical assessments. In this prospective study, a motion capture system was used to quant...
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Veröffentlicht in: | Clinical anatomy (New York, N.Y.) N.Y.), 2023-04, Vol.36 (3), p.492-502 |
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creator | Sarhan, François‐Régis Olivetto, Matthieu Ben Mansour, Khalil Neiva, Cécilia Colin, Emilien Choteau, Baptiste Marie, Jean‐Paul Testelin, Sylvie Marin, Frédéric Dakpé, Stéphanie |
description | Most techniques for evaluating unilateral impairments in facial movement yield subjective measurements. The objective of the present study was to define a reference dataset and develop a visualization tool for clinical assessments. In this prospective study, a motion capture system was used to quantify facial movements in 30 healthy adults and 2 patients. We analyzed the displacements of 105 reflective markers placed on the participant's face during five movements (M1–M5). For each marker, the primary endpoint was the maximum amplitude of displacement from the static position (M0) in an analysis of variance. The measurement precision was 0.1 mm. Significant displacements of markers were identified for M1–M5, and displacement patterns were defined. The patients and age‐matched healthy participants were compared with regard to the amplitude of displacement. We created a new type of radar plot to visually represent the diagnosis and facilitate effective communication between medical professionals. In proof‐of‐concept experiments, we collected quantitative data on patients with facial palsy and created a patient‐specific radar plot. Our new protocol for clinical facial motion capture (“quantified analysis of facial movement,” QAFM) was accurate and should thus facilitate the long‐term clinical follow‐up of patients with facial palsy. To take account of the limitations affecting the comparison with the healthy side, we created a dataset of healthy facial movements; our method might therefore be applicable to other conditions in which movements on one or both sides of the face are impaired. The patient‐specific radar plot enables clinicians to read and understand the results rapidly. |
doi_str_mv | 10.1002/ca.23999 |
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The objective of the present study was to define a reference dataset and develop a visualization tool for clinical assessments. In this prospective study, a motion capture system was used to quantify facial movements in 30 healthy adults and 2 patients. We analyzed the displacements of 105 reflective markers placed on the participant's face during five movements (M1–M5). For each marker, the primary endpoint was the maximum amplitude of displacement from the static position (M0) in an analysis of variance. The measurement precision was 0.1 mm. Significant displacements of markers were identified for M1–M5, and displacement patterns were defined. The patients and age‐matched healthy participants were compared with regard to the amplitude of displacement. We created a new type of radar plot to visually represent the diagnosis and facilitate effective communication between medical professionals. In proof‐of‐concept experiments, we collected quantitative data on patients with facial palsy and created a patient‐specific radar plot. Our new protocol for clinical facial motion capture (“quantified analysis of facial movement,” QAFM) was accurate and should thus facilitate the long‐term clinical follow‐up of patients with facial palsy. To take account of the limitations affecting the comparison with the healthy side, we created a dataset of healthy facial movements; our method might therefore be applicable to other conditions in which movements on one or both sides of the face are impaired. 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Clinical Anatomy published by Wiley Periodicals LLC on behalf of American Association of Clinical Anatomists and British Association of Clinical Anatomists.</rights><rights>2023. This article is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). 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The objective of the present study was to define a reference dataset and develop a visualization tool for clinical assessments. In this prospective study, a motion capture system was used to quantify facial movements in 30 healthy adults and 2 patients. We analyzed the displacements of 105 reflective markers placed on the participant's face during five movements (M1–M5). For each marker, the primary endpoint was the maximum amplitude of displacement from the static position (M0) in an analysis of variance. The measurement precision was 0.1 mm. Significant displacements of markers were identified for M1–M5, and displacement patterns were defined. The patients and age‐matched healthy participants were compared with regard to the amplitude of displacement. We created a new type of radar plot to visually represent the diagnosis and facilitate effective communication between medical professionals. In proof‐of‐concept experiments, we collected quantitative data on patients with facial palsy and created a patient‐specific radar plot. Our new protocol for clinical facial motion capture (“quantified analysis of facial movement,” QAFM) was accurate and should thus facilitate the long‐term clinical follow‐up of patients with facial palsy. To take account of the limitations affecting the comparison with the healthy side, we created a dataset of healthy facial movements; our method might therefore be applicable to other conditions in which movements on one or both sides of the face are impaired. 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The objective of the present study was to define a reference dataset and develop a visualization tool for clinical assessments. In this prospective study, a motion capture system was used to quantify facial movements in 30 healthy adults and 2 patients. We analyzed the displacements of 105 reflective markers placed on the participant's face during five movements (M1–M5). For each marker, the primary endpoint was the maximum amplitude of displacement from the static position (M0) in an analysis of variance. The measurement precision was 0.1 mm. Significant displacements of markers were identified for M1–M5, and displacement patterns were defined. The patients and age‐matched healthy participants were compared with regard to the amplitude of displacement. We created a new type of radar plot to visually represent the diagnosis and facilitate effective communication between medical professionals. In proof‐of‐concept experiments, we collected quantitative data on patients with facial palsy and created a patient‐specific radar plot. Our new protocol for clinical facial motion capture (“quantified analysis of facial movement,” QAFM) was accurate and should thus facilitate the long‐term clinical follow‐up of patients with facial palsy. To take account of the limitations affecting the comparison with the healthy side, we created a dataset of healthy facial movements; our method might therefore be applicable to other conditions in which movements on one or both sides of the face are impaired. 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subjects | Adult Amplitudes Datasets Displacement facial anatomy facial asymmetry Facial Expression facial movement Facial Muscles Facial Paralysis - diagnosis Healthy Volunteers Human health and pathology Humans kinematics Life Sciences Medical personnel mimics motion analysis Motion capture Movement Paralysis Patients Position measurement Prospective Studies Radar three‐dimensional Variance analysis |
title | Quantified analysis of facial movement: A reference for clinical applications |
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