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Auteur Norou DIAWARA |
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A pilot study to identify autism related traits in spontaneous facial actions using computer vision / Manar D. SAMAD in Research in Autism Spectrum Disorders, 65 (September 2019)
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Titre : A pilot study to identify autism related traits in spontaneous facial actions using computer vision Type de document : Texte imprimé et/ou numérique Auteurs : Manar D. SAMAD, Auteur ; Norou DIAWARA, Auteur ; Jonna L. BOBZIEN, Auteur ; Cora M. TAYLOR, Auteur ; John W. HARRINGTON, Auteur ; Khan M. IFTEKHARUDDIN, Auteur Article en page(s) : p.14-24 Langues : Anglais (eng) Mots-clés : ASD Behavioral marker Differential traits Facial action units Computer vision Spontaneous expressions Index. décimale : PER Périodiques Résumé : Background Individuals with autism spectrum disorders (ASD) may be differentiated from typically developing controls (TDC) based on phenotypic features in spontaneous facial expressions. Computer vision technology can automatically track subtle facial actions to gain quantitative insights into ASD related behavioral abnormalities. Method This study proposes a novel psychovisual human-study to elicit spontaneous facial expressions in response to a variety of social and emotional contexts. We introduce a markerless facial motion capture and computer vision methods to track spontaneous and subtle activations of facial muscles. The facial muscle activations are encoded into ten representative facial action units (FAU) to gain quantitative, granular, and contextual insights into the psychophysical development of the participating individuals. Statistical tests are performed to identify differential traits in individuals with ASD after comparing those in a cohort of age-matched TDC individuals. Results The proposed framework has revealed significant difference (p?0.001) in the activation of ten FAU and contrasting activations of FAU between the group with ASD and the TDC group. Unlike the TDC group, the group with ASD has shown unusual prevalence of mouth frown (FAU 15) and low correlations in temporal activations of several FAU pairs: 6–12, 10–12, and 10–20. The interpretation of different FAU activations suggests quantitative evidence of expression bluntness, lack of expression mimicry, incongruent reaction to negative emotions in the group with ASD. Conclusion Our generalized framework may be used to quantify psychophysical traits in individuals with ASD and replicate in similar studies that require quantitative measurements of behavioral responses. En ligne : https://doi.org/10.1016/j.rasd.2019.05.001 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=401
in Research in Autism Spectrum Disorders > 65 (September 2019) . - p.14-24[article] A pilot study to identify autism related traits in spontaneous facial actions using computer vision [Texte imprimé et/ou numérique] / Manar D. SAMAD, Auteur ; Norou DIAWARA, Auteur ; Jonna L. BOBZIEN, Auteur ; Cora M. TAYLOR, Auteur ; John W. HARRINGTON, Auteur ; Khan M. IFTEKHARUDDIN, Auteur . - p.14-24.
Langues : Anglais (eng)
in Research in Autism Spectrum Disorders > 65 (September 2019) . - p.14-24
Mots-clés : ASD Behavioral marker Differential traits Facial action units Computer vision Spontaneous expressions Index. décimale : PER Périodiques Résumé : Background Individuals with autism spectrum disorders (ASD) may be differentiated from typically developing controls (TDC) based on phenotypic features in spontaneous facial expressions. Computer vision technology can automatically track subtle facial actions to gain quantitative insights into ASD related behavioral abnormalities. Method This study proposes a novel psychovisual human-study to elicit spontaneous facial expressions in response to a variety of social and emotional contexts. We introduce a markerless facial motion capture and computer vision methods to track spontaneous and subtle activations of facial muscles. The facial muscle activations are encoded into ten representative facial action units (FAU) to gain quantitative, granular, and contextual insights into the psychophysical development of the participating individuals. Statistical tests are performed to identify differential traits in individuals with ASD after comparing those in a cohort of age-matched TDC individuals. Results The proposed framework has revealed significant difference (p?0.001) in the activation of ten FAU and contrasting activations of FAU between the group with ASD and the TDC group. Unlike the TDC group, the group with ASD has shown unusual prevalence of mouth frown (FAU 15) and low correlations in temporal activations of several FAU pairs: 6–12, 10–12, and 10–20. The interpretation of different FAU activations suggests quantitative evidence of expression bluntness, lack of expression mimicry, incongruent reaction to negative emotions in the group with ASD. Conclusion Our generalized framework may be used to quantify psychophysical traits in individuals with ASD and replicate in similar studies that require quantitative measurements of behavioral responses. En ligne : https://doi.org/10.1016/j.rasd.2019.05.001 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=401