A Predictive Model for Automatic Detection of Loneliness and Social Isolation Using Machine Learning

Authors

  • Amado Scott Bello-Valle TECNM Centro Nacional de Investigación y Desarrollo Tecnológico
  • Alicia Martínez-Rebollar TECNM Centro Nacional de Investigación y Desarrollo Tecnológico
  • Wendy Sánchez TECNM Instituto Tecnológico de Matamoros
  • Hugo Estrada-Esquivel TECNM Centro Nacional de Investigación y Desarrollo Tecnológico

DOI:

https://doi.org/10.13053/cys-26-1-4157

Keywords:

Predictive model, loneliness, social isolation, elderly

Abstract

In Mexico, elderly is the group with the highest growth rate in the entire country. In 2010, the elderly represented 8.8% of the population and it is estimated that by 2050, they will represent 28% of the estimated population. This demographic change represents several challenges for current social programs that intend to maintain the independence of elderly in families and in their community. The problem of the development of emotional and psychological disorders in older adults can be associated with the prevalence of affective, cognitive, and behavioral disorders. In most cases, these medical conditions are not properly diagnosed or treated. This situation is currently a research topic of novel approaches to improve the well-being and quality of life of this segment of the population. The objective of research work presented in this paper is to develop a predictive model of loneliness and social isolation from the information obtained from the monitoring of the daily activities of an older adult.

Downloads

Published

2022-03-26

Issue

Vol. 26 No. 1 (2022): Recent Advances in Language & Knowledge Engineering (Guest editors: D. Pinto, B. Beltrán, A. Vázquez, D. Vilariño)

Section

Articles of the Thematic Issue

License 

Hereby I transfer exclusively to the Journal "Computación y 
Sistemas", published by the Computing Research Center (CIC-IPN),
the Copyright of the aforementioned paper. I also accept that these 
rights will not be transferred to any other publication, in any other 
format, language or other existing means of developing.
I certify that the paper has not been previously disclosed or simultaneo
usly submitted to any other publication, and that it does not contain 
material whose publication would violate the Copyright or other 
proprietary rights of any person, company or institution. I certify that 
I have the permission from the institution or company where I work or 
study to publish this work.
The representative author accepts the responsibility for the publication
of this paper on behalf of each and every one of the authors. 
This transfer is subject to the following conditions:
  • The authors retain all ownership rights (such as patent rights) of this work, except for the publishing rights transferred to the CIC, through this document.
  • Authors retain the right to publish the work in whole or in part in any book they are the authors or publishers. They can also make use of this work in conferences, courses, personal web pages, and so on.
  • Authors may include working as part of his thesis, for non-profit distribution only.