Artificial Vision Algorithm for Behavior Recognition in Children with ADHD in a Smart Home Environment

Jonnathan Berrezueta-Guzman, Stephan Krusche, Luis Serpa-Andrade, María Luisa Martín-Ruiz

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Artificial vision has made a great advance in the recognition of visual patterns that are not perceptible by humans or that are biased in their interpretation. Among its applications, artificial vision or computer vision has served in the support of people with some kind of disability. In this work, an image classification algorithm is developed to complement a pervasive therapy support system for children with Attention Deficit Hyperactivity Disorder (ADHD) during the development of their homework. For this purpose, a camera is adapted within a smart environment made up of Smart objects and a robotic assistant. In the system, a convolutional neural network (CNN) is implemented for the classification of the child’s status (doing or not doing his/her homework). An experiment of this implementation is carried out in which the results of the environment without the camera are compared with the results obtained by using the camera and the implemented CNN. The latter results are also compared with the information collected through observation by the therapist during the session. The results show that what the camera identifies as the child not doing homework matches what the smart objects identify as distractions and pauses at 82.70% and what the therapist identifies as distractions and pauses at 98.21%. This approach will help the smart home environment have new and more accurate data to process and make better decisions, just like a therapist would do.

Original languageEnglish
Title of host publicationIntelligent Systems and Applications - Proceedings of the 2022 Intelligent Systems Conference IntelliSys Volume 1
EditorsKohei Arai
PublisherSpringer Science and Business Media Deutschland GmbH
Pages661-671
Number of pages11
ISBN (Print)9783031160714
DOIs
StatePublished - 2023
EventIntelligent Systems Conference, IntelliSys 2022 - Virtual, Online
Duration: 1 Sep 20222 Sep 2022

Publication series

NameLecture Notes in Networks and Systems
Volume542 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

ConferenceIntelligent Systems Conference, IntelliSys 2022
CityVirtual, Online
Period1/09/222/09/22

Bibliographical note

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

  • ADHD
  • Artificial vision
  • Computer vision
  • Convolutional neural networks
  • Robotics
  • Smart home

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