The new system, known as PAViS, can be used remotely by healthcare workers to view sleep profiles and analyse sleep patterns based on sensory data gathered at the patient’s home.
Sleep disturbance is one of the most distressing symptoms in Alzheimer’s disease and might also be an early indicator of the onset of the disease in some cases, explained lead researcher Dr Huiru Zheng from the Computer Science Research Institute.
She said: “There are almost half a million people in the UK with Alzheimer’s disease and for many of those sleep disorders and disruptive nocturnal behaviour present a significant clinical problem for healthcare workers and are a cause of distress for caregivers. The ‘telecare’ systems allow healthcare workers to monitor patient activity whether in normal or supported housing.
“Sleep-related problems generally worsen as the disease progresses and are an indicator of cognitive impairment and lead to the patient being less alert than would be expected during waking hours as well as reducing their overall wellbeing.
“Various systems have been developed in recent years to monitor sleeping patients. However, these would often tend to involve other people in the patient’s home as well as simply monitoring sleep patterns rather than long-term monitoring and analysis of sleep profiles for assessing sleep quality.
“PAViS, pattern analysis and visualisation system, circumvents the problems and allows healthcare workers to quickly see shifts in sleep pattern and detect unusual patterns in order to assess the changes in health condition of people with early dementia over the course of weeks and months. Data are collected from infrared movement detectors and sensors on bedroom and other doors in the patient’s home. This provides a non-invasive, pervasive and objective monitoring and assessment solution.”
The University of Ulster’s research team, based at the Jordanstown campus, has been working with the Fold Housing Association in Holywood, County Down, on a trial basis with a small number of patient case studies to demonstrate proof of principle in monitoring a patient’s total amount of sleep time, sleep episodes and their rhythm of sleep.
Researchers found that it was relatively easy to distinguish between the sleep patterns of a non-Alzheimer’s patient with only one or two sleeping ‘episodes’, big movements, such as getting out of bed during the night reflecting many hours of undisturbed sleep. This compares with 35 episodes or more in Alzheimer’s patients and many fewer hours of total sleeping time.
“PAViS provides a tool to enable telecare service and carers to be able to have a better overview of the client’s behaviour so as to provide sufficient support when necessary,” said Dr Zheng.
“While current telecare service focuses on providing telemonitoring of clients’ daily activity, and tries to detect abnormal behaviour, it is also important to investigate the correlation of behaviour profile, such as sleep pattern profile, with the clients’ health condition. The knowledge discovered or obtained from the long-term sleep profiles can also be used to support intervention in detecting and responding to abnormal sleep pattern.”
Details of this research project were published this month’s issue of the International Journal of Computers in Healthcare.
For further information, please contact: