Early Diagnose of Autism Spectrum Disorder Using Machine Learning Based on Simple Upper Limb Movements

Mohammad Wedyan, Adel Al-Jumaily, Alessandro Crippa

Research output: Chapter in Book/Report/Conference proceedingConference contribution


The importance of early diagnosis of autism that leads to early intervention such thing shall increase the results of treating it. The Autism Spectrum Disorder (ASD) affects the children activities and caused difficulties in interaction, impairments in communication, delayed speech, and weak eye contact. These activities used as the base for ASD diagnosis decision. Children move their upper limb before some of the other activities. Moving upper limb can be based for ASD diagnosis decision for autistic children. Such paper examines diagnosing the ASD that depends on motioning the children’s upper-limb aged between two and four years based on executing specific procedures and machine learning. The approach that such study utilized is both (LDA) Linear Discriminant Analysis in order to elicit the features and (SVM) Support Vector Machines for classifying thirty children such study selected fifteen autistic children out of fifteen non-autistic children by testing the collected data that are collected from doing an easy task. The results of such study have accomplished an optimal sortation accuracy of 100% and the average accuracy of 93.8%. Such outcomes provide more proof of simple brachium motioning that might be utilized in sorting poor performance of autistic children precisely.

Original languageEnglish
Title of host publicationHybrid Intelligent Systems - 18th International Conference on Hybrid Intelligent Systems HIS 2018
EditorsMaria Leonilde Varela, Ana Maria Madureira, Niketa Gandhi, Ajith Abraham
PublisherSpringer Verlag
Number of pages10
ISBN (Print)9783030143466
Publication statusPublished - Jan 1 2020
Event18th International Conference on Hybrid Intelligent Systems, HIS 2018 - Porto, Portugal
Duration: Dec 13 2018Dec 15 2018

Publication series

NameAdvances in Intelligent Systems and Computing
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365


Conference18th International Conference on Hybrid Intelligent Systems, HIS 2018


  • Autism
  • Autistic children
  • Early autism detection
  • LDA
  • SVM

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

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