What is it about?

Face movements can be indicators of disease severity in ALS. Clinical evaluation of facial movements is time-consuming and requires expertise. This work explores the use of AI to automatically evaluate facial movements from videos and predict disease severity in people with ALS.

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Why is it important?

Results from this paper demonstrated that motor function assessments obtained from videos using AI methods agree with clinician scores. Our findings indicate that AI systems for video analysis have the potential to transform the assessment of movement disabilities in ALS and other neurodegenerative diseases. These systems could support clinical disease management by providing fast and accurate methods to assess patients even from their homes.

Perspectives

This article shows that AI video analysis methods can potentially transform clinicians' assessment of motor deficits. We are working to bring these tools to the users so that people can perform a clinically validated motor assessment from their homes using a personal computer.

Diego Guarin
University of Florida

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This page is a summary of: Video-Based Facial Movement Analysis in the Assessment of Bulbar Amyotrophic Lateral Sclerosis: Clinical Validation, Journal of Speech Language and Hearing Research, December 2022, American Speech-Language-Hearing Association (ASHA), DOI: 10.1044/2022_jslhr-22-00072.
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