Approaches for meltdown detection in children with autism: a scoping review

  • Zakia Turabee*
  • , David Brown
  • , Mufti Mahmud
  • , Andreas Oikonomou
  • , Andrew Burton
  • , Nicholas Shopland
  • , Muhammad Arifur Rahman
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose – The purpose of this paper is to review studies relevant to the early identification of behavioural changes in children with autism when they start to feel overwhelmed and use their detection for the timely launch of evidence-based well-being interventions for their mitigation. Design/methodology/approach – A scoping review of electronic databases was undertaken focusing on the studies related to emotions or arousal detection in children with Autism. Findings – The literature selected for this research explores different methodologies used for detecting precursors of emotional dysregulation (termed meltdown) in individuals with autism. Results suggest that use of multi-modal data is an under researched area, further compounded by the lack of accessible state of the art data sets. Originality/value – This paper is first of its type aiming to review and categorise existing literature related to approaches for emotion and arousal detection in children with Autism to identify gaps where contemporary computer science methods may help.

Original languageEnglish
JournalJournal of Enabling Technologies
DOIs
StateAccepted/In press - 2025

Bibliographical note

Publisher Copyright:
© Emerald Publishing Limited

Keywords

  • ASC
  • Arousal
  • Autism
  • Behavioural data
  • Emotional dysregulation
  • Engagement
  • Physiological signals
  • Rumble moments
  • Tracking
  • Wearables

ASJC Scopus subject areas

  • Health(social science)
  • Rehabilitation
  • Computer Science Applications
  • Management of Technology and Innovation

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