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Technological solution of psychological therapies using neural networks for the control and monitoring of anxiety disorder

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

Abstract

This article proposes a technological solution for the control and monitoring of anxiety disorder behavior in vulnerable populations that allows receiving symptomatology data, tests and manifestations in real time during psychological therapies The result of this research seeks to optimize the time of attention and to monitor patients in psychological therapies through the use of neural networks and the systematization of psychological tests. This proposal consists of 4 phases: 1. Collection of test results and alerts; 2. Reception of the collected information; 3. The technological solution was validated in a community mental health center in the district of San Martin de Porres in Lima, Peru. Preliminary results showed that technological solution allows to reduce time of psychological therapies by 25% and has an efficiency of 80% based on the tests performed.

Original languageEnglish
Title of host publicationProceedings of the 2021 IEEE Sciences and Humanities International Research Conference, SHIRCON 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665429146
DOIs
StatePublished - 2021
Event5th IEEE Sciences and Humanities International Research Conference, SHIRCON 2021 - Lima, Peru
Duration: 17 Nov 202119 Nov 2021

Publication series

NameProceedings of the 2021 IEEE Sciences and Humanities International Research Conference, SHIRCON 2021

Conference

Conference5th IEEE Sciences and Humanities International Research Conference, SHIRCON 2021
Country/TerritoryPeru
CityLima
Period17/11/2119/11/21

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Anxiety Disorder
  • Children
  • Monitoring System
  • Neural Network
  • Symptom Collection

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