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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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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. |
format | Online Article Text |
id | pubmed-9566798 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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