ArticleJournal of speech, language, and hearing research : JSLHR2023
3D Video Tracking Technology in the Assessment of Orofacial Impairments in Neurological Disease: Clinical Validation.
Article in Journal of speech, language, and hearing research : JSLHR, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Objective Dynamic Assessment of Facial Movement Asymmetry in Children Using a Marker-Based Video Method.Journal of clinical medicine · 2026Article
- 3-D Markerless Tracking of Speech Movements With Submillimeter Accuracy.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2026Article
- A multimodal approach to automated hierarchical assessment of bulbar involvement in amyotrophic lateral sclerosis.Frontiers in neurology · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
purposeThis study sought to determine whether clinically interpretable kinematic features extracted automatically from three-dimensional (3D) videos were correlated with corresponding perceptual clinical orofacial ratings in individuals with orofacial impairments due to neurological disorders.
method45 participants (19 diagnosed with motor neuron diseases [MNDs] and 26 poststroke) performed two nonspeech tasks (mouth opening and lip spreading) and one speech task (repetition of a sentence "Buy Bobby a Puppy") while being video-recorded in a standardized lab setting. The color video recordings of participants were assessed by an expert clinician-a speech language pathologist-on the severity of three orofacial measures: symmetry, range of motion (ROM), and speed. Clinically interpretable 3D kinematic features, linked to symmetry, ROM, and speed, were automatically extracted from video recordings, using a deep facial landmark detection and tracking algorithm for each of the three tasks. Spearman correlations were used to identify features that were significantly correlated (
resultsSeveral kinematic features extracted from 3D video recordings were associated with their corresponding perceptual clinical scores, indicating clinical validity of these automatically derived measures. Different patterns of significant features were observed between MND and poststroke groups; these differences were aligned with clinical expectations in both cases.
conclusionsThe results show that kinematic features extracted automatically from simple clinical tasks can capture characteristics used by clinicians during assessments. These findings support the clinical validity of video-based automatic extraction of kinematic features.
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