Using Indoor Movement Complexity in Smart Homes to Detect Frailty in Older Adults: Multiple-Methods Case Series Study.
Abstract
The theory of complexity in aging indicates that the complexity of sensor-derived physiological and behavioral signals reflects an older adult's adaptive capacity and, in turn, their frailty. Smart homes with ambient sensors offer a unique opportunity to longitudinally explore the complexity of older adults' indoor movement in a real-world setting. Here, we introduce a computational method to estimate behavior complexity from sensor data. We further conduct a multiple-methods case series to explore the relationship between entropy-measured smart home data complexity and older adult frailty.
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Research summary
The paper claims that the complexity of indoor movement data can be used to detect frailty in older adults. This research is relevant as it explores innovative methods to assess frailty, which is a significant aspect of aging and can contribute to understanding adaptive capacities in older adults.
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