Pattern visualisation and knowledge discovery for interpreting activity behaviors within smart home environments
To promote independent living for elders and people with chronic diseases, there is growing interest in the role played by community services, which are supported by assistive technologies . As a means by which care and support can be provided through the use of electronics, telecommunications and information systems, the significance of telecare has been recognized in wide spectrum of applications ranging from triggering alarms through to monitoring of vital signs and activities both in the home and on the move. While a large amount of data have been collected in smart home environments and research has been focused on activity recognition and monitoring, little has been carried out on the representation, visualisation and interpreting a user’s activity behaviour profile, in relating to with his/her life style and health conditions, for example, the changes of sleep patterns with the dementia condition.
The objectives of this project are to develop interactive pattern visualisation tools for activity trend monitoring supported by intelligent data analysis, to investigate the correlation of activity profiles with user’s health conditions, and to extract knowledge from activity profiles to support the user self management and telecare service. Data to be used in this study are generated from intelligent sensors from telecare smart home environments with long term monitoring .
It is envisaged that inter-disciplinary (clinical and telecare service) collaborations will support the development of this project.
For additional information please contact Dr. Huiru (Jane) Zheng (h.zheng@ulster.ac.uk).
[1] Hoda Nikamalfard, Huiru Zheng, Haiying Wang, Paul Jeffers, Maurice Mulevena, et al, “Knowledge Discovery from Activity Monitoring to Support Independent Living of People with Early Dementia,” IEEE-EMBS International Conference on Biomedical and Health Informatics 2012, Hong Kong, 2-7 Jan 2012, pp. 910-913
[2] Hoda Nikamalfard, Huiru Zheng, Haiying Wang, Maurice Mulvenna, Paul McCullagh, Paul Jeffers, "A sleep pattern analysis and visualization system to support people with early dementia," 5th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) 2011, vol., no., pp.510-513, 23-26 May 2011
[3] Haiying Wang, Huiru Zheng, Juan Augusto, Suzanne Martin, Maurice Mulvenna, William Carswell, Jonathan Wallace, Paul Jeffers, Barbara Taylor and Kevin McSorley, “Monitoring and analysis of sleep pattern for people with early dementia”, in Proceedings of 2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops, 18-21 December , Hong Kong, pp. 405 – 410
[4] Hine N, Judson A, Ashraf S et al, “Modelling the Behaviour of Elderly People as a Means of Monitoring Well Being”, in User Modeling 2005, Springer, pp. 241 – 250
Personnel Involved
First Supervisor: Zheng, H Dr
Second Supervisor: Wang, HY Dr
Third Supervisor: McCullagh, PJ Dr
Collaboration: This project does not involve collaboration with another establishment