Muestra métricas de impacto externas asociadas a la publicación. Para mayor detalle:
| Indexado |
|
||||
| DOI | 10.3390/S23010268 | ||||
| Año | 2023 | ||||
| Tipo | artículo de investigación |
Citas Totales
Autores Afiliación Chile
Instituciones Chile
% Participación
Internacional
Autores
Afiliación Extranjera
Instituciones
Extranjeras
In Chile, 18% of the population is over 60 years old and is projected to reach 31% in three decades. An aging population demands the development of strategies to improve quality of life (QoL). In this randomized trial, we present the implementation and evaluation of the Quida platform, which consists of a network of unintrusive sensors installed in the houses of elderly participants to monitor their activities and provide assistance. Sixty-nine elderly participants were included. A significant increase in overall QoL was observed amongst participants allocated to the interventional arm (p < 0.02). While some studies point out difficulties monitoring users at home, Quida demonstrates that it is possible to detect presence and movement to identify patterns of behavior in the sample studied, allowing us to visualize the behavior of older adults at different time intervals to support their medical evaluation.
| Ord. | Autor | Género | Institución - País |
|---|---|---|---|
| 1 | TARAMASCO-TORO, CARLA | Mujer |
Universidad Nacional Andrés Bello - Chile
Núcleo Milenio de Sociomedicina - Chile |
| 2 | RIMASSA-VASQUEZ, CARLA GIOVANNA | Mujer |
Universidad de Valparaíso - Chile
Universidad Nacional Andrés Bello - Chile |
| 3 | MARTINEZ-LOMAKIN, FELIPE | Hombre |
Universidad Nacional Andrés Bello - Chile
Concentra Investigación y Educación Biomédica - Chile Concentra Invest & Educ Biomed - Chile |
| Fuente |
|---|
| Fondo Nacional de Desarrollo Científico y Tecnológico |
| Agencia Nacional de Investigación y Desarrollo |
| National Research and Development Agency |
| Agradecimiento |
|---|
| This work was supported by the National Research and Development Agency (ANID) through the project FONDECYT Regular 1201787 (multimodal machine learning approach for detecting pathological activity patterns in elderly people). It also received contributions from the ANID Millennium Nucleus of the Sociomedicine Program N° NCS2021_013. |