Using Low-Resolution Non-Invasive Infrared Sensors to Classify Activities and Falls in Older Adults

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 solut...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2022-03, Vol.22 (6), p.2321
Main Authors: Márquez, Gastón, Veloz, Alejandro, Minonzio, Jean-Gabriel, Reyes, Claudio, Calvo, Esteban, Taramasco, Carla
Format: Article
Language:English
Subjects:
Accelerometers
Accidental Falls - prevention & control
Adults
Aged
Aging
Algorithms
Artificial intelligence
Classification
Data integrity
Deep learning
Energy consumption
fall
Fall detection
Falls
Gait
Humans
Humidity
infrared sensor
Medical equipment
Mortality
Neural networks
older adult
Older people
Physicians
Privacy
Quality of Life
Sensors
Smart buildings
Smart houses
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Summary: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.
ISSN:1424-8220
1424-8220
DOI:10.3390/s22062321