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Monitoring and Analysis of Sleep Patterns of People with Dementia

Wang, HY, Zheng, Huiru and Mulvenna, Maurice (2015) Monitoring and Analysis of Sleep Patterns of People with Dementia. In: International Psychogeriatric Association (IPA) International Annual Congress, Berlin. IPA. 4 pp. [Conference contribution]

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The quantity and quality of sleep has a direct impact on the quality of life for people with dementia and their carers. Many research questions remain to be explored: (1) How to monitor and assess the quantity and quality of sleep objectively and ubiquitously? (2) How does sleep pattern change over the course of various disease types? (3) What variables should be used to assess sleep patterns? (4) What feedback format can be used in telecare service? And (5) What support can be provided to ameliorate sleep disturbances suffered by people with dementia?The main interest to telecare service is to monitoring shifts in sleep patterns and to flag the unusual patterns, so as to observe the changes of clients’ health condition. In this study we examine three types of sleep information: quantity, quality, and rhythm. The bed sensor and the PIR sensors are triggered by the events in seconds. Events such as turning over in bed could trigger the bed sensor and the bedroom PIR sensor. To remove this type of short time trigger and extract the in-bed and out-of-bed events, various rules were applied. Visual feedback is one of the key issues in telecare systems, as telecare staff and the clients’ carers may be novice ICT users. A total of n=8 individual participants with dementia completed the 3 month final evaluation phase of the project with fully deployed systems. The different sleep patterns observed between the clients are consistent with the clinical observation that most people with dementia suffer sleep disturbance, have more sleep episodes and lower sleep quality. It is feasible to detect unusual sleep patterns and monitor the trend of the changes. This system could also be used to provide information for the prevention of the risks of other mental health issues that might be triggered by the sleep disorder.

Item Type:Conference contribution (Paper)
Keywords:Assistive Technology, Dementia
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Research Institutes and Groups:Computer Science Research Institute > Smart Environments
Computer Science Research Institute
Computer Science Research Institute > Artificial Intelligence and Applications
ID Code:32596
Deposited By: Professor Maurice Mulvenna
Deposited On:19 Nov 2015 10:51
Last Modified:19 Nov 2015 10:51

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