Using Low-Resolution Non-Invasive Infrared Sensors to Classify Activities and Falls in Older Adults.
Sensors (Basel)
; 22(6)2022 Mar 17.
Article
em En
| MEDLINE
| ID: mdl-35336493
ABSTRACT
The population is aging worldwide, creating new challenges to the quality of life of older adults and their families. Falls are an increasing, but not inevitable, threat to older adults. Information technologies provide several solutions to address falls, but smart homes and the most available solutions require expensive and invasive infrastructures. In this study, we propose a novel approach to classify and detect falls of older adults in their homes through low-resolution infrared sensors that are affordable, non-intrusive, do not disturb privacy, and are more acceptable to older adults. Using data collected between 2019 and 2020 with the eHomeseniors platform, we determine activity scores of older adults moving across two rooms in a house and represent an older adult fall through skeletonization. We find that our twofold approach effectively detects activity patterns and precisely identifies falls. Our study provides insights to physicians about the daily activities of their older adults and could potentially help them make decisions in case of abnormal behavior.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Qualidade de Vida
/
Acidentes por Quedas
Tipo de estudo:
Prognostic_studies
Limite:
Aged
/
Humans
Idioma:
En
Ano de publicação:
2022
Tipo de documento:
Article