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Deep Mobile Linguistic Therapy for Patients with ASD

Author

Listed:
  • Ari Ernesto Ortiz Castellanos

    (College of Electrical Engineering and Computer Science, National Taipei University of Technology, Taipei City 106, Taiwan
    These authors contributed equally to this work.)

  • Chuan-Ming Liu

    (Department of Computer Science and Information Engineering, National Taipei University of Technology, Taipei City 106, Taiwan
    These authors contributed equally to this work.)

  • Chongyang Shi

    (School of Computer Science and Technology, Beijing Institute of Technology, Beijing 102488, China
    These authors contributed equally to this work.)

Abstract

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.

Suggested Citation

  • Ari Ernesto Ortiz Castellanos & Chuan-Ming Liu & Chongyang Shi, 2022. "Deep Mobile Linguistic Therapy for Patients with ASD," IJERPH, MDPI, vol. 19(19), pages 1-17, October.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:19:p:12857-:d:935791
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