Abstract
In recent years, the ultra-wideband (UWB) radar technology has shown great potential in monitoring activities of daily living (ADLs) for smart homes. In this paper, we investigate the significance of using non-wearable UWB sensors for developing non-intrusive, unobtrusive, and privacy-preserving monitoring of elderly ADLs. A controlled experiment was setup, implementing multiple non-wearable sensors in a smart home Lab setting. A total of nine (n = 9) participants were involved in conducting predefined scenarios of ADLs- cooking, eating, resting, sleeping and mobility. We employed the UWB sensing prototype and conventional implementation technologies, and the sensed data of both systems were stored, analysed and their performances were compared. The result shows that the performance of the non-wearable UWB technology is as good as that of the conventional ones. Furthermore, we provided a proof-of-concept solution for the real-time detection of abnormal behaviour based on excessive activity levels, and a model for automatic alerts to caregivers for timely medical assistance on-demand.
Highlights
Trends show that the population of developing nations is growing older than ever before
This work investigated the development of a context-aware, non-wearable UWB sensing prototype capable of recognizing activities of daily living (ADL)
A controlled experiment was performed in a smart-home laboratory setting which allowed us to measure the ability of the technologies to detect and to classify the participants’ daily activities through simulation of predefined scenarios- cooking, eating, resting, sleeping, and mobility
Summary
Trends show that the population of developing nations is growing older than ever before. This is due to the increase in life expectancy and lower birth-rates [1,2,3]. This trend will inevitably lead to a shortage in both nursing home spots and healthcare personnel while simultaneously increasing the demand for elderly care due to age-related diseases [4]. This triggers a demand for an evaluation of a person’s ability to function independently when performing the activities of daily living (ADLs). The ubiquitous and automated sensing of elderly activities, behaviour, physiological and cognitive abilities has received notable attention in the ambient assisted living (AAL) research domain [5]
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