ICT Framework for Supporting Applied Behavior Analysis in the Social Inclusion of Children with Neurodevelopmental Disorders

Sensors (Basel). 2023 Aug 3;23(15):6914. doi: 10.3390/s23156914.

Abstract

The applied behavior analysis (ABA) model emphasizes observable and measurable behaviors by carrying out decision making using experimental data (behavioral observation assessment strategies). In this framework, information and communication technology (ICT) becomes highly suitable for enhancing the efficiency and effectiveness of the methodology. This paper aims to delve into the potential of ICT in providing innovative solutions to support ABA applications. It focuses on how ICT can contribute to fostering social inclusion with respect to children with neurodevelopmental disorders. ICT offers advanced solutions for continuous and context-aware monitoring, as well as automatic real-time behavior assessments. Wireless sensor systems (wearable perceptual, biomedical, motion, location, and environmental sensors) facilitate real-time behavioral monitoring in various contexts, enabling the collection of behavior-related data that may not be readily evident in traditional observational studies. Moreover, the incorporation of artificial intelligence algorithms that are appropriately trained can further assist therapists throughout the different phases of ABA therapy. These algorithms can provide intervention guidelines and deliver an automatic behavioral analysis that is personalized to the child's unique profile. By leveraging the power of ICT, ABA practitioners can benefit from cutting-edge technological advancements to optimize their therapeutic interventions and outcomes for children with neurodevelopmental disorders, ultimately contributing to their social inclusion and overall wellbeing.

Keywords: ABA; ICT; Information and communication technologies; applied behavior analysis; children with neurodevelpmental disorders; social inclusion; wireless communications.

MeSH terms

  • Applied Behavior Analysis*
  • Artificial Intelligence
  • Child
  • Communication
  • Humans
  • Neurodevelopmental Disorders* / diagnosis
  • Neurodevelopmental Disorders* / therapy
  • Social Inclusion

Grants and funding

This work was supported in part by the European Telecommunications Standards Institute (ETSI) SmartBAN, by the European Union’s Horizon 2020 Research and Innovation Programme under Grants 872752 and 101017331, and by Fondazione Cassa di Risparmio di Firenze (project: SmartHUB on Medical & Social ICT for Territorial Assistance).