Augusto, JC, Martin, Suzanne, Mulvenna, Maurice, Carswell, William and Zheng, Huiru (2010) Holistic Night-Time Care. Gerontechnology, 9 (2). pp. 109-110. [Journal article]
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Assisted living systems for healthcare are being developed as part of the fundamental shift from hospital-centred to home-centred models of care within health services. These systems are supported by Smart Environments, physical environments enriched with sensing and actuating devices, e.g., smart homes. Most of the contributions reported in the technical literature focus on the most active period of the day (daylight time). Our project NOCTURNAL (Night Optimised Care Technology for UseRs Needing Assisted Lifestyles) assumes that the night period and daylight periods of the day are different enough to require separate analysis. At night time, people with dementia can experience fearfulness and anxiety which can lead to restlessness, physically threatening behaviour, ‘wandering’, and disruption of normal behaviour (feeding, sleeping and hygiene). Methods. A number of different approaches have been tried. A literature study shows that technology can play a pivotal role providing assistance to people with dementia during night time. However, these studies focused on monitoring a specific aspect of the night time activity or applying a single technology to aid people with dementia during the night. Our work builds upon the current setup commercial telecare offerings and provides additional features. Several of these additional features focus around providing greater guidance. Smart sensing and guidance algorithms will help control the lights and support navigational guidance at night time. A primary goal of the work is to encourage good sleeping habits through a combination of movement sensors (bed and infra-red based) that detect movement in sleep augmented by a combination of changing light levels and music. An important, multi-functional feature for each dwelling will include a bedside audio visual unit. This unit will form a type of Avatar with extra input received from the array of sensors located throughout the house. The audio visual unit will be able to collect the in-house sensor information and form a Decision Support Structure (DSS) choosing the appropriate response. The unit can also display pictures and play music for reminiscence therapy, which has also been proven to alleviate anger, confusion and tension. Discussion. At night, a person with dementia will be more likely to be in an environment where disorientation is more likely and natural due to low light conditions. Also, the person with dementia is more likely to be confused and disorientated as they awaken, naturally as they awake from sleep. Therefore it can be argued that, for people with dementia, their need for assistive technology at night more be more acute. The use of light and music together with conventional assistive technologies for support of people at night is novel, and can provide powerful intervention capability. Lighting can also play an important role in reducing the risk of falls, in particular when people with dementia seek to go to the bathroom and back. In terms of applying algorithms and decision support to night-time activity data, there are fewer activities of living experienced during night time, and most of the activity is in the bedroom and bath-room therefore the complexity of the system to recognise the basic behaviours from data should not be increased. However there may be a paucity of data as activities at night may be sparse. Furthermore the underlying purpose of the acts that generate the sensor data may be more difficult to infer than during daytime, arising from activities carried out when the person with dementia is confused and or anxious. The opportunities for research for nocturnal care of people with dementia using holistic assistive technologies are for more specialised algorithms to infer behaviour from sparse data; specially designed interventions perhaps including music and video, that provide therapeutic support to people to reduce anxiety; and sophisticated guidance, through the use of lightning.
|Item Type:||Journal article|
|Faculties and Schools:||Faculty of Computing & Engineering|
Faculty of Computing & Engineering > School of Computing and Mathematics
Faculty of Life and Health Sciences
Faculty of Life and Health Sciences > School of Health Sciences
|Research Institutes and Groups:||Institute of Nursing and Health Research > Centre for Health and Rehabilitation Technologies|
Computer Science Research Institute
Computer Science Research Institute > Artificial Intelligence and Applications
|Deposited By:||Professor Maurice Mulvenna|
|Deposited On:||21 Feb 2011 15:46|
|Last Modified:||28 Feb 2012 11:57|
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