RTLA-HAR: a model proposal based on reinforcement and transfer learning for the adaptation of learning in human activity recognition

The Assisted Living Environment Research Area – AAL (Ambient Assisted Living), focuses on generating innovative technology, products, and services to assist medical attention and rehabilitation to the elderly, with the purpose of increasing the time in which these people can live independently, sinc...

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Autores:
Ariza Colpas, Paola Patricia
Oviedo Carrascal, Ana Isabel
aziz, shariq
Piñeres Melo, Marlon Alberto
Tipo de recurso:
Article of investigation
Fecha de publicación:
2023
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/10572
Acceso en línea:
https://hdl.handle.net/11323/10572
https://repositorio.cuc.edu.co/
Palabra clave:
Human Activity Recognition – HAR
Activities of Daily Living – ADL
Selection techniques
Classification techniques
Smart home
Rights
embargoedAccess
License
Atribución 4.0 Internacional (CC BY 4.0)
Description
Summary:The Assisted Living Environment Research Area – AAL (Ambient Assisted Living), focuses on generating innovative technology, products, and services to assist medical attention and rehabilitation to the elderly, with the purpose of increasing the time in which these people can live independently, since whether or not they suffer from neurodegenerative diseases or a disability. This important area is responsible for the development of systems for the recognition of activity - ARS (Activity Recognition Systems) which are a valuable tool when identifying the type of activity carried out by the elderly, in order to provide them with effective assistance that allows you to carry out daily activities with total normality. This article aims to show the review of the literature and the evolution of the different data mining techniques applied to this health sector, by showing the metrics of recent experiments for researchers in this area of knowledge. The objective of this article is to carry out the review of highly relevant research works in terms of learning based on reinforcement and transfer, to later outline the different components of the RTLHAR model, for the identification and adaptation of learning focused on the recognition of human activities.