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ICT Framework for Supporting Applied Behavior Analysis in the Social Inclusion of Children with Neurodevelopmental Disorders
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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10422576/ https://www.ncbi.nlm.nih.gov/pubmed/37571692 http://dx.doi.org/10.3390/s23156914 |
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author | Jayousi, Sara Martinelli, Alessio Lucattini, Paolo Mucchi, Lorenzo |
author_facet | Jayousi, Sara Martinelli, Alessio Lucattini, Paolo Mucchi, Lorenzo |
author_sort | Jayousi, Sara |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10422576 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-104225762023-08-13 ICT Framework for Supporting Applied Behavior Analysis in the Social Inclusion of Children with Neurodevelopmental Disorders Jayousi, Sara Martinelli, Alessio Lucattini, Paolo Mucchi, Lorenzo Sensors (Basel) Article 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. MDPI 2023-08-03 /pmc/articles/PMC10422576/ /pubmed/37571692 http://dx.doi.org/10.3390/s23156914 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Jayousi, Sara Martinelli, Alessio Lucattini, Paolo Mucchi, Lorenzo ICT Framework for Supporting Applied Behavior Analysis in the Social Inclusion of Children with Neurodevelopmental Disorders |
title | ICT Framework for Supporting Applied Behavior Analysis in the Social Inclusion of Children with Neurodevelopmental Disorders |
title_full | ICT Framework for Supporting Applied Behavior Analysis in the Social Inclusion of Children with Neurodevelopmental Disorders |
title_fullStr | ICT Framework for Supporting Applied Behavior Analysis in the Social Inclusion of Children with Neurodevelopmental Disorders |
title_full_unstemmed | ICT Framework for Supporting Applied Behavior Analysis in the Social Inclusion of Children with Neurodevelopmental Disorders |
title_short | ICT Framework for Supporting Applied Behavior Analysis in the Social Inclusion of Children with Neurodevelopmental Disorders |
title_sort | ict framework for supporting applied behavior analysis in the social inclusion of children with neurodevelopmental disorders |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10422576/ https://www.ncbi.nlm.nih.gov/pubmed/37571692 http://dx.doi.org/10.3390/s23156914 |
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