This paper presents the development of a sensor network for measuring the well-being of people with dementia (PwD) and assessing the progression of the disease throughout the overall course of the dementia. To gain an insight into the overall well-being of a PwD, sensors can provide information about multiple aspects, such as the level of social, cognitive and physical activities and abilities. The proposed measurement system is minimally invasive and can be adapted to different built environments and allows to monitor human behavior under multiple aspects such as lifestyle monitoring, sleep analysis, social interaction, and human localization. The core technology of the chosen sensor network is made of a GPS tracker, a lifestyle monitoring sensor network, a social tablet and a smart mattress for sleep monitoring. These sensors collect data that built a heterogeneous dataset, that can be used in combination with artificial intelligence (AI) algorithms that can be trained to predict PwD well-being and extract more useful information, such as the progression of the dementia disease. The proposed solution is intended to reduce and support the workload of formal carers, since the progression of the dementia decreases PwD well-being, increases the caregiver burden and possibly decreases the quality of care

Heterogeneous sensor network for the measurement of dementia progression and well-being: preliminary study

Morresi N.;Revel G. M.;Casaccia S.
2022

Abstract

This paper presents the development of a sensor network for measuring the well-being of people with dementia (PwD) and assessing the progression of the disease throughout the overall course of the dementia. To gain an insight into the overall well-being of a PwD, sensors can provide information about multiple aspects, such as the level of social, cognitive and physical activities and abilities. The proposed measurement system is minimally invasive and can be adapted to different built environments and allows to monitor human behavior under multiple aspects such as lifestyle monitoring, sleep analysis, social interaction, and human localization. The core technology of the chosen sensor network is made of a GPS tracker, a lifestyle monitoring sensor network, a social tablet and a smart mattress for sleep monitoring. These sensors collect data that built a heterogeneous dataset, that can be used in combination with artificial intelligence (AI) algorithms that can be trained to predict PwD well-being and extract more useful information, such as the progression of the dementia disease. The proposed solution is intended to reduce and support the workload of formal carers, since the progression of the dementia decreases PwD well-being, increases the caregiver burden and possibly decreases the quality of care
978-1-6654-8299-8
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/306168
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