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Automatic Assessment of Motor Impairments in Autism Spectrum Disorders: A Systematic Review

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Abstract

Autism spectrum disorder (ASD) is mainly described as a disorder of communication and socialization. However, motor abnormalities are also common in ASD. New technologies may offer quantitative and automatic metrics to measure movement difficulties. We sought to identify computational methods to automatize the assessment of motor impairments in ASD. We systematically searched for the terms ’autism’, ’movement’, ’automatic’, ’computational’ and ’engineering’ in IEEE (Institute of Electrical and Electronics Engineers), Medline and Scopus databases and reviewed the literature from inception to 2018. We included all articles discussing: (1) automatic assessment/new technologies, (2) motor behaviours and (3) children with ASD. We excluded studies that included patient’s or parent’s reported outcomes as online questionnaires that focused on computational models of movement, but also eye tracking, facial emotion or sleep. In total, we found 53 relevant articles that explored static and kinetic equilibrium, like posture, walking, fine motor skills, motor synchrony and movements during social interaction that can be impaired in individuals with autism. Several devices were used to capture relevant motor information such as cameras, 3D cameras, motion capture systems, accelerometers. Interestingly, since 2012, the number of studies increased dramatically as technologies became less invasive, more precise and more affordable. Open-source software has enabled the extraction of relevant data. In a few cases, these technologies have been implemented in serious games, like “Pictogram Room”, to measure the motor status and the progress of children with ASD. Movement computing opens new perspectives for patient assessment in ASD research, enabling precise characterizations in experimental and at-home settings, and a better understanding of the role of sensorimotor disturbances in the development of social cognition and ASD. These methods would likely enable researchers and clinicians to better distinguish ASD from other motors disorders while facilitating an improved monitoring of children’s progress in more ecological settings (i.e. at home or school).

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Abbreviations

ASD:

Autism spectrum disorder

ADI:

Autism Diagnostic Interview-Revised

ADOSő-2:

Autism Diagnostic Observation Schedule -2

BHK:

Concise Evaluation Scale for Children’s Handwriting

BOT-2:

Bruininks-Oseretsky Test of Motor Proficiency

CARS:

Childhood Autism Rating Scale

CNN:

Convolutional Neural Network

DBD:

Developmental Behaviour Checklist

DCD:

Developmental coordination Disorder

DCDDaily-Q:

Developmental Coordination Disorder Daily-Questionnaire

DSM-5:

Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition

GARS:

Gilliam Autism Rating Scale

Hz:

Hertz

IEEE:

Institute of Electrical and Electronics Engineers

ICBS:

Infant and Caregiver Behavior Scale

ICD-10:

International Classification of Disease

JA:

Joint Attention

MABC-2:

Movement Assessment Battery for Children

M-CHAT:

Modified Checklist for Autism in Toddlers

M-CHAT-R/F:

Modified Checklist for Autism in Toddlers, Revised with Follow-Up (M-CHAT- R/F)

MRI:

Magnetic Resonance Imagery

MSEL:

Mullen Scales of Early Learning

NDDs:

Neurodevelopmental Disorders

NDE:

Neuro-Developmental Engineering

NN:

Neural Networks

NP-MOT:

Neuro-Psychomotrian evaluation of the child

PAC:

Pedagogical Analysis and Curriculum

PDF:

Probability Density Functions

PEP-R:

Profil Psycho- Educatif (PsychoEducational Profile—Revised)

PRISMA:

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

RBS-R:

Stereotyped Behavior Subscale of the Repetitive Behavior Scale-Revised

RGB-D sensor:

Red, Green, Blue—Depth sensor

SRS:

Social Responsiveness Scale

SMM:

Stereotypical Motor Movements

SVM:

Support Vector Machine

TD children:

Typically Developing children

TGMD-2:

Test of Gross Motor Development

WASI:

Wechsler Abbreviated Scale of Intelligence

WISC:

Wechsler Intelligence Scale for Children

WPPSI:

Wechsler Preschool and Primary Scale of Intelligence

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Funding

The authors thank the Assistance Publique Hôpitaux de Paris, the Paris 8 University, the bilateral French-Swiss ANR-FNC project iReCheck (ANR-19-CE19-0029 - FNS 200021E_189475/1) funding and the Centre National de la Recherche Scientifique (CNRS) for financial support. We would like to thank the Swiss National Science Foundation for supporting this project through the National Center of Competence in Research Robotics. Part of this work is also supported by the LiLLaB (Living & Learning Lab Neuro-Development) financed by the Ministry of Higher Education, Research and Innovation in the context the French National Autism Strategy.

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  1. Thomas Gargot

    Present address: Centre Universitaire de Pédopsychiatrie EXcellence Center in Autism and neurodevelopmental disorders - Tours ExACT, iBrain U1253 Imagerie et Cerveau, Université François Rabelais, Tours, France

Authors and Affiliations

  1. Psychiatrie de l’Enfant et de l’Adolescent, Hôpital Universitaire Pitié Salpêtrière, Paris, France

    Thomas Gargot & David Cohen

  2. Institut des Systèmes Intelligents et Robotiques (ISIR, CNRS UMR7222), Sorbonne Université, Paris, France

    Thomas Gargot, Mohamed Chetouani & David Cohen

  3. Laboratoire Cognitions Humaine et Artificielle (CHArt EA4004), Université, Paris 8, Saint Denis, France

    Thomas Gargot, Dominique Archambault & Salvatore Maria Anzalone

  4. UNSW Sydney, Sydney, Australia

    Wafa Johal

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TG performed a first screening, selected the keywords, screened and selected the articles, designed the figures and wrote the first draft; DC proposed the general idea and wrote the first draft; SA designed the figures and revised the first draft; DA, MC and WJ revised the first draft; all authors read and approved the final manuscript.

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Gargot, T., Archambault, D., Chetouani, M. et al. Automatic Assessment of Motor Impairments in Autism Spectrum Disorders: A Systematic Review. Cogn Comput 14, 624–659 (2022). https://doi.org/10.1007/s12559-021-09940-8

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