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Deep Mobile Linguistic Therapy for Patients with ASD

Autistic spectrum disorder (ASD) is one of the most complex groups of neurobehavioral and developmental conditions. The reason is the presence of three different impaired domains, such as social interaction, communication, and restricted repetitive behaviors. Some children with ASD may not be able t...

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Detalles Bibliográficos
Autores principales: Ortiz Castellanos, Ari Ernesto, Liu, Chuan-Ming, Shi, Chongyang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9566798/
https://www.ncbi.nlm.nih.gov/pubmed/36232157
http://dx.doi.org/10.3390/ijerph191912857
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author Ortiz Castellanos, Ari Ernesto
Liu, Chuan-Ming
Shi, Chongyang
author_facet Ortiz Castellanos, Ari Ernesto
Liu, Chuan-Ming
Shi, Chongyang
author_sort Ortiz Castellanos, Ari Ernesto
collection PubMed
description Autistic spectrum disorder (ASD) is one of the most complex groups of neurobehavioral and developmental conditions. The reason is the presence of three different impaired domains, such as social interaction, communication, and restricted repetitive behaviors. Some children with ASD may not be able to communicate using language or speech. Many experts propose that continued therapy in the form of software training in this area might help to bring improvement. In this work, we propose a design of software speech therapy system for ASD. We combined different devices, technologies, and features with techniques of home rehabilitation. We used TensorFlow for Image Classification, ArKit for Text-to-Speech, Cloud Database, Binary Search, Natural Language Processing, Dataset of Sentences, and Dataset of Images with two different Operating Systems designed for Smart Mobile devices in daily life. This software is a combination of different Deep Learning Technologies and makes Human–Computer Interaction Therapy very easy to conduct. In addition, we explain the way these were connected and put to work together. Additionally, we explain in detail the architecture of software and how each component works together as an integrated Therapy System. Finally, it allows the patient with ASD to perform the therapy anytime and everywhere, as well as transmitting information to a medical specialist.
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spelling pubmed-95667982022-10-15 Deep Mobile Linguistic Therapy for Patients with ASD Ortiz Castellanos, Ari Ernesto Liu, Chuan-Ming Shi, Chongyang Int J Environ Res Public Health Article Autistic spectrum disorder (ASD) is one of the most complex groups of neurobehavioral and developmental conditions. The reason is the presence of three different impaired domains, such as social interaction, communication, and restricted repetitive behaviors. Some children with ASD may not be able to communicate using language or speech. Many experts propose that continued therapy in the form of software training in this area might help to bring improvement. In this work, we propose a design of software speech therapy system for ASD. We combined different devices, technologies, and features with techniques of home rehabilitation. We used TensorFlow for Image Classification, ArKit for Text-to-Speech, Cloud Database, Binary Search, Natural Language Processing, Dataset of Sentences, and Dataset of Images with two different Operating Systems designed for Smart Mobile devices in daily life. This software is a combination of different Deep Learning Technologies and makes Human–Computer Interaction Therapy very easy to conduct. In addition, we explain the way these were connected and put to work together. Additionally, we explain in detail the architecture of software and how each component works together as an integrated Therapy System. Finally, it allows the patient with ASD to perform the therapy anytime and everywhere, as well as transmitting information to a medical specialist. MDPI 2022-10-07 /pmc/articles/PMC9566798/ /pubmed/36232157 http://dx.doi.org/10.3390/ijerph191912857 Text en © 2022 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
Ortiz Castellanos, Ari Ernesto
Liu, Chuan-Ming
Shi, Chongyang
Deep Mobile Linguistic Therapy for Patients with ASD
title Deep Mobile Linguistic Therapy for Patients with ASD
title_full Deep Mobile Linguistic Therapy for Patients with ASD
title_fullStr Deep Mobile Linguistic Therapy for Patients with ASD
title_full_unstemmed Deep Mobile Linguistic Therapy for Patients with ASD
title_short Deep Mobile Linguistic Therapy for Patients with ASD
title_sort deep mobile linguistic therapy for patients with asd
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9566798/
https://www.ncbi.nlm.nih.gov/pubmed/36232157
http://dx.doi.org/10.3390/ijerph191912857
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