The Artificial Intelligence as a Technological Resource in the Application of Tasks for the Development of Joint Attention in Children with Autism | Springer Nature Link (formerly SpringerLink) Skip to main content Advertisement Log in Menu Find a journal Publish with us Track your research Search Cart Home Intelligent Systems Conference paper The Artificial Intelligence as a Technological Resource in the Application of Tasks for the Development of Joint Attention in Children with Autism Conference paper First Online: 12 October 2023 pp 306–320 Cite this conference paper Intelligent Systems (BRACIS 2023) Nathália Assis Valentim9, Fabiano Azevedo Dorça9, Valéria Peres Asnis9 & … Nassim Chamel Elias10  Show authors Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14195)) Included in the following conference series: Brazilian Conference on Intelligent Systems 632 Accesses 3 Citations Abstract People with autism spectrum disorder (ASD) may present, in addition to deficits in communication, social interaction and patterns of restricted and repetitive behaviors, also present a deficit in joint attention (JA), which refers to the response repertoire of following and/or directing an adult’s visual attention to objects or events in the environment. By having a strong relationship with the learning process, joint attention deficits can compromise a person’s learning process. In this way, the use of technology can help in the development of abilities in people with autism, such as, for example, improving joint attention, communication and social skills. In this context, the general objective of the work proposal was to develop a computational approach for intervention that allows the interaction of the student with autism, with 4 and 5 years old, with deficit in joint attention and social-communicative difficulties. Artificial intelligence (AI) techniques were used to model the most appropriate sequence and level of complexity of exercises for each child. AI resources were used with the intention of providing an intelligent environment to guide the child, dynamically and adaptively, in order to promote stimuli and adequate personalization of the process. In this way, it is intended to contribute significantly to the advancement of the state of the art regarding the production of computational technologies for people with ASD. Supported by Research Support Foundation of the State of Minas Gerais (FAPEMIG) - UNIVERSAL DEMAND Process: APQ-00837-21. This research has an opinion embodied by the Research Ethics Committee number 5.273.182, with CAAE 54880921.7.0000.5152, the Proposing Institution being the Faculty of Computing of the Federal University of Uberlândia. This is a preview of subscription content, log in via an institution to check access. 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Autism spectrum disorders Computational Intelligence Developmental Disabilities Intelligence Augmentation Intelligence Development Artificial Intelligence References de Almeida, L.G.S.: Padrões de Projeto de Análise para Desenvolvimento de Software do Domínio do Transtorno do Espectro Autista (TEA). Master’s thesis, Universidade Federal Fluminense (2021) Google Scholar  American Psychiatric Association: DSM-5: manual diagnóstico e estatístico de transtornos mentais. Artmed Editora (2014) Google Scholar  Barsoum: Fer+ (face expression recognition plus dataset) (2017). https://github.com/Microsoft/FERPlus Barsoum, E., Zhang, C., Ferrer, C.C., Zhang, Z.: Training deep networks for facial expression recognition with crowd-sourced label distribution. In: ACM International Conference on Multimodal Interaction, pp. 279–283 (2016). https://doi.org/10.1145/2993148.2993165 Bates, E., Benigni, L., Bretherton, I., Camaioni, L., Volterra, V.: The Emergence of Symbols: Cognition and Communication in Infancy. Academic Press, New York (1979) Google Scholar  Cardon, T.A., Wilcox, M.J., Campbell, P.H.: Caregiver perspectives about assistive technology use with their young children with autism spectrum disorders. Infants Young Child. 24(2), 153–173 (2011). https://doi.org/10.1097/IYC.0b013e31820eae40 Article  Google Scholar  Elias, N.C.: Teorias comportamentais sobre a etiologia do autismo e uma nova proposta. UEL (2019) Google Scholar  Gera, D., Balasubramanian, S.: Landmark guidance independent spatio-channel attention and complementary context information based facial expression recognition. Pattern Recogn. Lett. 145, 58–66 (2021). https://doi.org/10.1016/j.patrec.2021.01.029 Article  Google Scholar  Ghahramani, Z.: Unsupervised learning. In: Bousquet, O., von Luxburg, U., Rätsch, G. (eds.) ML 2003. LNCS (LNAI), vol. 3176, pp. 72–112. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-28650-9_5 Chapter  MATH  Google Scholar  Goodfellow, I., Bengio, Y., Courville, A., Bengio, Y.: Deep Learning, vol. 1. MIT Press, Cambridge (2016) Google Scholar  Jia, Y., et al.: Caffe: convolutional architecture for fast feature embedding. In: ACM International Conference on Multimedia. Association for Computing Machinery (2014). https://doi.org/10.1145/2647868.2654889 Juárez-Ramírez, R., Navarro-Almanza, R., Gomez-Tagle, Y., Licea, G., Huertas, C., Quinto, G.: Orchestrating an adaptive intelligent tutoring system: towards integrating the user profile for learning improvement. Procedia. Soc. Behav. Sci. 106, 1986–1999 (2013). https://doi.org/10.1016/j.sbspro.2013.12.227 Article  Google Scholar  Chinea Manrique de Lara, A., Jiménez de Espinoza, C., González-Mora, J.: A fast automated diagnosis system for autism spectrum disorders based on eye tracking technology (2016). https://doi.org/10.13140/RG.2.2.32220.28809 Mordvintsev, A., Abid, K.: Opencv-python tutorials documentation (2014). https://media.readthedocs.org/pdf/opencv-python-tutroals/latest/opencv-python-tutroals.pdf Mundy, P., Delgado, C., Block, J., Venezia, M., Hogan, A., Seibert, J.: Early Social Communication Scales (ESCS). University of Miami, Coral Gables (2003) Google Scholar  Pavlov, N.: User interface for people with autism spectrum disorders. J. Softw. Eng. Appl. (2014). https://doi.org/10.4236/jsea.2014.72014 Article  Google Scholar  Pimenta, T.: Transtorno do espectro autista ou autismo: causas e tratamento (2018). https://www.vittude.com/blog/transtorno-do-espectro-autista-ou-autismo/. Accessed May 2019 Sherkatghanad, Z., et al.: Automated detection of autism spectrum disorder using a convolutional neural network. Front. Neurosci. 13 (2019). https://doi.org/10.3389/fnins.2019.01325 Tenório, M., Vasconcelos, N.: Autismo: a tecnologia como ferramenta assistiva ao processo de ensino e aprendizagem de uma criança dentro do espectro. CINTEDI-Práticas pedagógicas direitos humanos e interculturalidade (2015) Google Scholar  Valentim, N.A.: Experiment data (2022). https://l1nk.dev/experimentdata. Accessed Oct 2022 Vijayan, A., Janmasree, S., Keerthana, C., Syla, L.B.: A framework for intelligent learning assistant platform based on cognitive computing for children with autism spectrum disorder. In: International CET Conference on Control, Communication, and Computing, pp. 361–365 (2018). https://doi.org/10.1109/CETIC4.2018.8530940 Download references Acknowledgement I offer my sincerest gratitude to my right arm Research Support Foundation of the State of Minas Gerais (FAPEMIG) - UNIVERSAL DEMAND Process: APQ-00837-21. Author information Authors and Affiliations Universidade Federal de Uberlândia, Uberlândia, Minas Gerais, Brazil Nathália Assis Valentim, Fabiano Azevedo Dorça & Valéria Peres Asnis Universidade Federal de São Carlos, São Carlos, São Paulo, Brazil Nassim Chamel Elias Authors Nathália Assis ValentimView author publications Search author on:PubMed Google Scholar Fabiano Azevedo DorçaView author publications Search author on:PubMed Google Scholar Valéria Peres AsnisView author publications Search author on:PubMed Google Scholar Nassim Chamel EliasView author publications Search author on:PubMed Google Scholar Corresponding author Correspondence to Nathália Assis Valentim . Editor information Editors and Affiliations Federal University of São Carlos, São Carlos, Brazil Murilo C. Naldi Centro Universitario da FEI, São Bernardo do Campo, Brazil Reinaldo A. C. Bianchi Rights and permissions Reprints and permissions Copyright information © 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG About this paper Cite this paper Valentim, N.A., Dorça, F.A., Asnis, V.P., Elias, N.C. (2023). The Artificial Intelligence as a Technological Resource in the Application of Tasks for the Development of Joint Attention in Children with Autism. In: Naldi, M.C., Bianchi, R.A.C. (eds) Intelligent Systems. BRACIS 2023. Lecture Notes in Computer Science(), vol 14195. Springer, Cham. https://doi.org/10.1007/978-3-031-45368-7_20 Download citation .RIS .ENW .BIB DOI: https://doi.org/10.1007/978-3-031-45368-7_20 Published: 12 October 2023 Publisher Name: Springer, Cham Print ISBN: 978-3-031-45367-0 Online ISBN: 978-3-031-45368-7 eBook Packages: Computer ScienceComputer Science (R0) Share this paper Anyone you share the following link with will be able to read this content: Get shareable linkSorry, a shareable link is not currently available for this article. 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