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Quantifying the social symptoms of autism using motion capture

Autism Spectrum Disorder (ASD) is a remarkably heterogeneous condition where individuals exhibit a variety of symptoms at different levels of severity. Quantifying the severity of specific symptoms is difficult, because it either requires long assessments or observations of the ASD individual, or re...

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Autores principales: Budman, Ian, Meiri, Gal, Ilan, Michal, Faroy, Michal, Langer, Allison, Reboh, Doron, Michaelovski, Analya, Flusser, Hagit, Menashe, Idan, Donchin, Opher, Dinstein, Ilan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6531432/
https://www.ncbi.nlm.nih.gov/pubmed/31118483
http://dx.doi.org/10.1038/s41598-019-44180-9
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author Budman, Ian
Meiri, Gal
Ilan, Michal
Faroy, Michal
Langer, Allison
Reboh, Doron
Michaelovski, Analya
Flusser, Hagit
Menashe, Idan
Donchin, Opher
Dinstein, Ilan
author_facet Budman, Ian
Meiri, Gal
Ilan, Michal
Faroy, Michal
Langer, Allison
Reboh, Doron
Michaelovski, Analya
Flusser, Hagit
Menashe, Idan
Donchin, Opher
Dinstein, Ilan
author_sort Budman, Ian
collection PubMed
description Autism Spectrum Disorder (ASD) is a remarkably heterogeneous condition where individuals exhibit a variety of symptoms at different levels of severity. Quantifying the severity of specific symptoms is difficult, because it either requires long assessments or observations of the ASD individual, or reliance on care-giver questionnaires, which can be subjective. Here we present a new technique for objectively quantifying the severity of several core social ASD symptoms using a motion capture system installed in a clinical exam room. We present several measures of child-clinician interaction, which include the distance between them, the proportion of time that the child approached or avoided the clinician, and the direction that the child faced in relation to the clinician. Together, these measures explained ~30% of the variance in ADOS scores, when using only ~5 minute segments of “free play” from the recorded ADOS assessments. These results demonstrate the utility of motion capture for aiding researchers and clinicians in the assessment of ASD social symptoms. Further development of this technology and appropriate motion capture measures for use in kindergartens and at home is likely to yield valuable information that will aid in quantifying the initial severity of core ASD symptoms and their change over time.
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spelling pubmed-65314322019-05-30 Quantifying the social symptoms of autism using motion capture Budman, Ian Meiri, Gal Ilan, Michal Faroy, Michal Langer, Allison Reboh, Doron Michaelovski, Analya Flusser, Hagit Menashe, Idan Donchin, Opher Dinstein, Ilan Sci Rep Article Autism Spectrum Disorder (ASD) is a remarkably heterogeneous condition where individuals exhibit a variety of symptoms at different levels of severity. Quantifying the severity of specific symptoms is difficult, because it either requires long assessments or observations of the ASD individual, or reliance on care-giver questionnaires, which can be subjective. Here we present a new technique for objectively quantifying the severity of several core social ASD symptoms using a motion capture system installed in a clinical exam room. We present several measures of child-clinician interaction, which include the distance between them, the proportion of time that the child approached or avoided the clinician, and the direction that the child faced in relation to the clinician. Together, these measures explained ~30% of the variance in ADOS scores, when using only ~5 minute segments of “free play” from the recorded ADOS assessments. These results demonstrate the utility of motion capture for aiding researchers and clinicians in the assessment of ASD social symptoms. Further development of this technology and appropriate motion capture measures for use in kindergartens and at home is likely to yield valuable information that will aid in quantifying the initial severity of core ASD symptoms and their change over time. Nature Publishing Group UK 2019-05-22 /pmc/articles/PMC6531432/ /pubmed/31118483 http://dx.doi.org/10.1038/s41598-019-44180-9 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Budman, Ian
Meiri, Gal
Ilan, Michal
Faroy, Michal
Langer, Allison
Reboh, Doron
Michaelovski, Analya
Flusser, Hagit
Menashe, Idan
Donchin, Opher
Dinstein, Ilan
Quantifying the social symptoms of autism using motion capture
title Quantifying the social symptoms of autism using motion capture
title_full Quantifying the social symptoms of autism using motion capture
title_fullStr Quantifying the social symptoms of autism using motion capture
title_full_unstemmed Quantifying the social symptoms of autism using motion capture
title_short Quantifying the social symptoms of autism using motion capture
title_sort quantifying the social symptoms of autism using motion capture
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6531432/
https://www.ncbi.nlm.nih.gov/pubmed/31118483
http://dx.doi.org/10.1038/s41598-019-44180-9
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