RESUMO
BACKGROUND: The Decade of Healthy Aging (2021-2030) emerges as a 10 years strategy to improve the lives of older adults, their families, and the communities in which they live. One of the actions defined in this framework is related to improving the measurement, monitoring, and understanding of characteristics, factors, and needs related to aging and health. The aim was to analyze and assess the process of construction and development of the Strategic Information System on Health, Funcional Dependence and Aging (SIESDE, for its acronym in Spanish). SIESDE will provide strategic information in Mexico at the municipal, state, and national levels that support the public policies on healthy aging. METHODS: The system processes and analyzes the data sources of the Health Information Systems and the National System of Statistical and Geographical Information. SIESDE comprises three components: (1) Design, construction, and evaluation of the indicators; (2) storage, management, and visualization, and (3) diffusion and translation of information. RESULTS: A total of 135 indicators were built on seven themes: (1) demographic, socioeconomic, and aging conditions, (2) health, (3) functional dependence, (4) healthy aging, (5) health services, (6) social and physical environments, and (7) complex indicators. CONCLUSIONS: SIESDE is an effective system for providing an overall view of health, aging, and functional dependence.
Assuntos
Envelhecimento Saudável , Humanos , México , Idoso , Nível de Saúde , Sistemas de Informação em Saúde , Envelhecimento , Idoso de 80 Anos ou maisRESUMO
Today, computer vision algorithms are very important for different fields and applications, such as closed-circuit television security, health status monitoring, and recognizing a specific person or object and robotics. Regarding this topic, the present paper deals with a recent review of the literature on computer vision algorithms (recognition and tracking of faces, bodies, and objects) oriented towards socially assistive robot applications. The performance, frames per second (FPS) processing speed, and hardware implemented to run the algorithms are highlighted by comparing the available solutions. Moreover, this paper provides general information for researchers interested in knowing which vision algorithms are available, enabling them to select the one that is most suitable to include in their robotic system applications.