A New Method for Stimulating Memory and Visual-Motor Coordination in Older Adults Through Basic Electronics Learning

Adrián Cabrera-Bermeo, Paúl Sebastian-Idrovo, Vladimir Robles-Bykbaev

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

Abstract

The aging of the population is a global challenge that brings with it a significant increase in problems related to cognitive health and quality of life in older adults. With increasing life expectancy, concern about cognitive decline has become a pressing issue. This problem not only affects the independence and well-being of older adults, but also places significant strain on health care systems and social resources. Cognitive decline, ranging from memory loss to decreased visual-motor coordination, represents a critical threat to the autonomy and quality of life of this ever-growing population. As society ages, there is a pressing need for innovative approaches that effectively address this challenge. In response to this pressing issue, an innovative approach has been developed that addresses these challenges comprehensively. Our research focuses on teaching basic electronics as a tool for cognitive stimulation in older adults. To achieve this, a wizard has been designed that uses the advanced YOLOv5 (You Only Look Once Version 5) model, a deep learning object recognition algorithm. We collected images of each key electronic component to train the model, which has enabled the assistant to accurately infer whether a circuit is correctly assembled or not. This methodology aims to enhance motor skills, improve visual-motor coordination and fine motor skills of older adults, contributing significantly to their quality of life and slowing down the process of cognitive decline. The results of our research have demonstrated encouraging metrics, indicating its potential practical utility. This underlines the importance of practical evaluation when adapting the YOLOv5 model for specific object detection applications. In the context of an aging population, our holistic approach presents a promising solution, focusing on improving the autonomy and well-being of older adults. This comprehensive approach offers an innovative solution to address the challenges of an aging population, while highlighting the importance of promoting the autonomy and well-being of older adults.

Original languageEnglish
Title of host publicationInformation Technology and Systems - ICITS 2024
EditorsAlvaro Rocha, Jorge Hochstetter Diez, Carlos Ferras, Mauricio Dieguez Rebolledo
PublisherSpringer Science and Business Media Deutschland GmbH
Pages193-202
Number of pages10
ISBN (Print)9783031542343
DOIs
StatePublished - 2024
EventInternational Conference on Information Technology and Systems, ICITS 2024 - Temuco, Chile
Duration: 24 Jan 202426 Jan 2024

Publication series

NameLecture Notes in Networks and Systems
Volume932 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

ConferenceInternational Conference on Information Technology and Systems, ICITS 2024
Country/TerritoryChile
CityTemuco
Period24/01/2426/01/24

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Keywords

  • computer vision
  • Senior citizens
  • visuomotor coordination and memory
  • YOLOv5 model

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