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Post published on Twitter/X on 11 May 2022 05:12

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An Bin Cho, Karen Otte, Irina Baskow, Felicitas Ehlen, Tolou Maslahati, Sebastian Mansow-Model, Tanja Schmitz-Hübsch, Behnoush Behnia, et al. (2022). Motor signature of autism spectrum disorder in adults without intellectual impairment. Scientific Reports, 12(1), 7670. Springer Science and Business Media LLC.

Publication date
10 May 2022
Identifier
10.1038/s41598-022-10760-5
Authors
An Bin Cho, Karen Otte, Irina Baskow, Felicitas Ehlen, Tolou Maslahati, Sebastian Mansow-Model, Tanja Schmitz-Hübsch, Behnoush Behnia, Stefan Roepke
Source
Scientific Reports
Details
12(1), 7670
Reference type
article
Publisher
Springer Science and Business Media LLC
Metadata source
crossref

Abstract

Abstract Motor signs such as dyspraxia and abnormal gait are characteristic features of autism spectrum disorder (ASD). However, motor behavior in adults with ASD has scarcely been quantitatively characterized. In this pilot study, we aim to quantitatively examine motor signature of adults with ASD without intellectual impairment using marker-less visual-perceptive motion capture. 82 individuals (37 ASD and 45 healthy controls, HC) with an IQ > 85 and aged 18 to 65 years performed nine movement tasks and were filmed by a 3D-infrared camera. Anatomical models were quantified via custom-made software and resulting kinematic parameters were compared between individuals with ASD and HCs. Furthermore, the association between specific motor behaviour and severity of autistic symptoms (Autism Diagnostic Observation Schedule 2, Autism Spectrum Quotient) was explored. Adults with ASD showed a greater mediolateral deviation while walking, greater sway during normal, tandem and single leg stance, a reduced walking speed and cadence, a greater arrhythmicity during jumping jack tasks and an impaired manual dexterity during finger tapping tasks (p 0.48) compared to HC. Furthermore, in the ASD group, some of these parameters correlated moderately to severity of ASD symptoms. Adults with ASD seem to display a specific motor signature in this disorder affecting movement timing and aspects of balance. The data appear to reinforce knowledge about motor signs reported in children and adolescents with ASD. Also, quantitative motor assessment via visual-perceptive computing may be a feasible instrument to detect subtle motor signs in ASD and perhaps suitable in the diagnosis of ASD in the future.

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