Video Assessment to Detect Amyotrophic Lateral Sclerosis.

Guilherme Camargo Oliveira, Quoc Cuong Ngo, Leandro Aparecido Passos, Leonardo Silva Oliveira, Stella Stylianou, João Paulo Papa, Dinesh Kumar

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Article in Digital biomarkers. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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7 authors.

Guilherme Camargo OliveiraSchool of Science, São Paulo State University, São Paulo, Brazil.

Quoc Cuong NgoSchool of Engineering, Royal Melbourne Institute of Technology, Melbourne, VIC, Australia.

Leandro Aparecido PassosSchool of Science, São Paulo State University, São Paulo, Brazil.

Leonardo Silva OliveiraSchool of Science, São Paulo State University, São Paulo, Brazil.

Stella StylianouSchool of Science, Royal Melbourne Institute of Technology, Melbourne, VIC, Australia.

João Paulo PapaSchool of Science, São Paulo State University, São Paulo, Brazil.

Dinesh KumarSchool of Engineering, Royal Melbourne Institute of Technology, Melbourne, VIC, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Weakened facial movements are early-stage symptoms of amyotrophic lateral sclerosis (ALS). ALS is generally detected based on changes in facial expressions, but large differences between individuals can lead to subjectivity in the diagnosis. We have proposed a computerized analysis of facial expression videos to detect ALS. Methods: This study investigated the action units obtained from facial expression videos to differentiate between ALS patients and healthy individuals, identifying the specific action units and facial expressions that give the best results. We utilized the Toronto NeuroFace Dataset, which includes nine facial expression tasks for healthy individuals and ALS patients. Results: The best classification accuracy was 0.91 obtained for the pretending to smile with tight lips expression. Conclusion: This pilot study shows the potential of using computerized facial expression analysis based on action units to identify facial weakness symptoms in ALS.

Indexed as

Amyotrophic lateral sclerosisFacial action unitsFacial expressionLogistic regressionMachine learning

Identifiers

PMID39473807

DOI10.1159/000540547

PMCPMC11521450

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