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A tailored smart home for dementia care.

Amiribesheli, M., 2017. A tailored smart home for dementia care. Doctoral Thesis (Doctoral). Bournemouth University.

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Abstract

Dementia refers to a group of chronic conditions that cause the permanent and gradual cognitive decline. Therefore, a Person with Dementia (PwD) requires constant care from various types of caregivers (e.g., informal, social and formal). It is commonly accepted that utilising Smart Homes (SH), as an instance of Ambient Assisted Living (AAL) technologies, for dementia care could potentially facilitate the care and consequently improve the quality of PwDs’ well-being. Nevertheless, most of the studies view dementia care as a straight application of standard SH technology without accommodating the specific requirements of dementia care. A consequence of this approach is the inadequacy and unacceptability of generic SH systems for the stakeholders of dementia care. This work considers the specific requirements of PwDs and their care circle in all development steps of an SH, such as design, implementation, and evaluation. It investigates how utilising novel design and computing approaches can enhance the quality of SHs for dementia care and consequently improve healthcare and wellbeing of PwDs. To do so, the thesis first studies the existing SHs for healthcare and identifies their drawbacks. Then, the requirements of dementia care stakeholders will be collected, analysed and reflected on in an SH system design. Extensions and adaptation of existing frameworks and technologies will be proposed to implement a prototype based on the design. Finally, a series of thorough evaluations and validation of the prototype will be carried out.

Item Type:Thesis (Doctoral)
Additional Information:If you feel that this work infringes your copyright, please contact the BURO Manager.
Uncontrolled Keywords:smart homes ; artificial intelligence ; machine learning ; knowledge representation ; health-care computing ; ambient intelligence ; advanced healthcare systems ; dementia technology
Group:Faculty of Science & Technology
ID Code:29789
Deposited By: Symplectic RT2
Deposited On:27 Sep 2017 09:48
Last Modified:09 Aug 2022 16:04

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