Department of Computer Science and Electronics, Universidad de la Costa CUC, Barranquilla 080002, Colombia.
Faculty of Engineering in Information and Communication Technologies, Universidad Pontificia Bolivariana, Medellín 050031, Colombia.
Sensors (Basel). 2022 Apr 29;22(9):3401. doi: 10.3390/s22093401.
The Assisted Living Environments Research Area-AAL (Ambient Assisted Living), focuses on generating innovative technology, products, and services to assist, medical care and rehabilitation to older adults, to increase the time in which these people can live. independently, whether they suffer from neurodegenerative diseases or some disability. This important area is responsible for the development of activity recognition systems-ARS (Activity Recognition Systems), which is a valuable tool when it comes to identifying the type of activity carried out by older adults, to provide them with assistance. that allows you to carry out your daily activities with complete normality. This article aims to show the review of the literature and the evolution of the different techniques for processing this type of data from supervised, unsupervised, ensembled learning, deep learning, reinforcement learning, transfer learning, and metaheuristics approach applied to this sector of science. health, showing the metrics of recent experiments for researchers in this area of knowledge. As a result of this article, it can be identified that models based on reinforcement or transfer learning constitute a good line of work for the processing and analysis of human recognition activities.
辅助生活环境研究领域-AAL（环境辅助生活），专注于生成创新技术、产品和服务，以辅助、医疗护理和康复老年人，增加这些人能够独立生活的时间。无论他们是否患有神经退行性疾病或某种残疾。这个重要的领域负责开发活动识别系统-ARS（活动识别系统），这是一种在识别老年人进行的活动类型方面非常有价值的工具，以便为他们提供帮助。这使他们能够正常地进行日常活动。本文旨在展示文献综述以及不同技术的演变，这些技术用于处理来自监督、无监督、集成学习、深度学习、强化学习、迁移学习和元启发式方法的数据，应用于健康科学的这一领域，展示了该领域研究人员最近实验的指标。作为这篇文章的结果，可以确定基于强化或迁移学习的模型是处理和分析人类识别活动的一个很好的工作方向。
