Data visualisation and data mining technology for supporting care for older people

The overall purpose of the research discussed here is the enhancement of home-based care by revealing individual patterns in the life of a person, through modelling of the "busyness" of activity in their dwelling, so that care can be better tailored to their needs and changing circumstances. The use of data mining and on-line analytical processing (OLAP) is potentially interesting in this context because of the possibility of exploring, detecting and predicting changes in the level of activity of people's movement that may reflect change in well-being. An investigation is presented here into the use of data mining and visualisation to illustrate activity from sensor data from a trial project run in a domestic context.

[1]  Jon Leachtenauer,et al.  Validation of rule-based inference of selected independent activities of daily living. , 2005, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.

[2]  S. Katz Studies of illness in the aged , 1963 .

[3]  Mark Perry,et al.  Multimodal and ubiquitous computing systems: supporting independent-living older users , 2004, IEEE Transactions on Information Technology in Biomedicine.

[4]  Diane J. Cook,et al.  The role of prediction algorithms in the MavHome smart home architecture , 2002, IEEE Wirel. Commun..

[5]  M. Fisk,et al.  Social alarms to telecare: Older people's services in transition , 2003 .

[6]  Norbert Noury,et al.  An Experimental Health Smart Home and Its Distributed Internet-based Information and Communication System: First Steps of a Research Project , 2001, MedInfo.

[7]  Stephen S. Intille,et al.  Designing a Home of the Future , 2002, IEEE Pervasive Comput..

[8]  S. Katz,et al.  STUDIES OF ILLNESS IN THE AGED. THE INDEX OF ADL: A STANDARDIZED MEASURE OF BIOLOGICAL AND PSYCHOSOCIAL FUNCTION. , 1963, JAMA.

[9]  B. Majeed,et al.  Automatic Intelligent Data Analysis in Sensor Networks for iSpace , 2004 .

[10]  Roy S. Kalawsky,et al.  Integrated Sensor Networks for Monitoring the Health and Well-Being of Vulnerable Individuals , 2006 .

[11]  Gregory D. Abowd,et al.  The Aware Home: A Living Laboratory for Ubiquitous Computing Research , 1999, CoBuild.

[12]  K Panico,et al.  Care in the community , 1995, Nature.

[13]  Donald E. Brown,et al.  Health-status monitoring through analysis of behavioral patterns , 2005, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[14]  Steve Brown,et al.  Modelling the Behaviour of Elderly People as a Means of Monitoring Well Being , 2005, User Modeling.

[15]  Petra Perner,et al.  Data Mining - Concepts and Techniques , 2002, Künstliche Intell..

[16]  Elizabeth D. Mynatt,et al.  Digital family portraits: supporting peace of mind for extended family members , 2001, CHI.

[17]  Nick Hine,et al.  Monitoring the Well‐being of Older People , 2007 .

[18]  M. Lawton,et al.  Assessment of older people: self-maintaining and instrumental activities of daily living. , 1969, The Gerontologist.

[19]  William C. Mann,et al.  The Gator Tech Smart House: a programmable pervasive space , 2005, Computer.