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

ABSTRACT

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.

REFERENCES

• 1: Age Concern Scotland. Older people in Scotland. Edinburgh, Scotland, UK, 2005. Online at: http://www.ageconcernscotland.org.uk/olderpeople/default.asp
• 2: Roper, N., Logan, W., and Tierney, A. The Roper-Logan-Tierney Model of Nursing. Churchill Livingstone, Edinburgh, Scotland, UK, 2000.
• 3: Scottish Executive. First Report for the Range and Capacity Review: Projections of Community Care Services Users, Workforce and Costs. Edinburgh, Scotland, UK, 2004.
• 4: Porteus, J. and Brownsell, S. A report on the Anchor Trust/BT Telecare Research Project. Anchor Trust, Oxon., England, UK, 2000.
• 5: Fisk, M. J. Social Alarms to Telecare. Older people's services in transition. The Policy Press, Bristol, England, UK, 2003.
• 6: Hine, N., Judson, A., Ashraf, A., Arnott, J. L., Sixsmith, A., Brown, S., and Garner, P. Modelling the Behaviour of Elderly People as a Means of Monitoring Well Being. In Proceedings of the 10th International Conference on User Modelling, Edinburgh, Scotland, UK, 2005, 241--250.
• 7: Cory D. Kidd , Robert Orr , Gregory D. Abowd , Christopher G. Atkeson , Irfan A. Essa , Blair MacIntyre , Elizabeth D. Mynatt , Thad Starner , Wendy Newstetter, The Aware Home: A Living Laboratory for Ubiquitous Computing Research, Proceedings of the Second International Workshop on Cooperative Buildings, Integrating Information, Organization, and Architecture, p.191-198, October 01-02, 1999
• 8: Stephen S. Intille, Designing a Home of the Future, IEEE Pervasive Computing, v.1 n.2, p.76-82, April 2002 [doi>10.1109/MPRV.2002.1012340 ]
• 9: Perry, M. and Dowdall, A. The Millennium Home: Domestic Technology to Support Independent-living Older People. The 1st Equator IRC Workshop on Ubiquitous Computing in Domestic Environments, (Nottingham, England, UK, September 13-14, 2001).
• 10: Perry, M., Dowdall, A., Lines, L., and Hone, K. Multimodal and ubiquitous computing systems: Supporting contextual interaction for older users in the home. IEEE Trans. Information Technology in Biomedicine, 8, 3, 2004, 258--270.
• 11: Sumi Helal , William Mann , Hicham El-Zabadani , Jeffrey King , Youssef Kaddoura , Erwin Jansen, The Gator Tech Smart House: A Programmable Pervasive Space, Computer, v.38 n.3, p.50-60, March 2005 [doi>10.1109/MC.2005.107]
• 12: Bauchet, J. Modelisation of ADLs in its environment for Cognitive Assistance. In Proceedings of 3rd International Conference on Smart Homes and Health Telematics (ICOST 2005) (Quebéc, Canada, July 4-6, 2005), 221--228.
• 13: Elizabeth D. Mynatt , Jim Rowan , Sarah Craighill , Annie Jacobs, Digital family portraits: supporting peace of mind for extended family members, Proceedings of the SIGCHI conference on Human factors in computing systems, p.333-340, March 2001, Seattle, Washington, United States [doi>10.1145/365024.365126]
• 14: Barger, T. S., Brown, D. E., and Alwan, M. Health-Status Monitoring Through Analysis of Behavioural Patterns. IEEE Trans. SMC Part A: Systems & Humans, 35, 1, 2005, 22--27.
• 15: Alwan, M., Leachtenauer, J. Dalal, S., Kell, S., Turner, B., Mack, D., and Felder, R. Case Report Validation of Rule-based Inference of Selected Independent Activities of Daily Living. Telemedicine and e-Health, 11, 5, 2005, 594--599.
• 16: S. Brown , N. Hine , A. Sixsmith , P. Garner, Care in the Community, BT Technology Journal, v.22 n.3, p.56-64, July 2004 [doi>10.1023/B:BTTJ.0000047120.60489.7a]
• 17: D. D. Nauck , B. Majeed, Automatic Intelligent Data Analysis in Sensor Networks for iSpace, BT Technology Journal, v.22 n.3, p.216-224, July 2004 [doi>10.1023/B:BTTJ.0000047135.14579.32]
• 18: Rialle, V., Noury, N., and Hervé, T. An experimental health smart home and its distributed internet-based information and communication system: First steps of a research project. In Proceedings of MEDINFO, London, England, UK, 2001, 1479--1483.
• 19: Das, S. K., Cook D. J., Bhattacharya, A., Heierman E. O., III, and Lin, T-Y. The role of prediction algorithms in the MavHome smart home architecture. IEEE Wireless Communications, 9, 6 (December 2002), 77--84.
• 20: Katz, S., Ford, A. B., Moskowitz, R. W., Thompson, H. M., and Svec, K. H. Studies of Illness in the Aged. The Index of ADL: a Standardized Measure of Biological and Psycho-social Function. Journal of the American Medical Association, 185, 1963, 914--919.
• 21: Lawton, M. Assessment of Older People: Self-Maintaining and Instrumental Activities of Daily Living. Gerontologist 9, 3, 1969, 179--186.
• 22: Sixsmith, A., Hine, N., Neild, I., Clarke, N., Brown, S., and Garner, P. Monitoring the well-being of older people. Topics in Geriatric Rehabilitation, 23, 1, 2007, 9--23.
• 23: Jiawei Han, Data Mining: Concepts and Techniques, Morgan Kaufmann Publishers Inc., San Francisco, CA, 2005
• 24: University of Waikato in New Zealand. Weka 3.5.3: Data Mining Software in Java, 2006. Online at: http://www.cs.waikato.ac.nz/ml/weka.
• 25: Heatley, D. J. T., Kalawsky, R. S., Neild, I., and Bowman P. A. Integrated Sensor Networks for Monitoring the Health and Well-Being of Vulnerable Individuals. In Steventon, A., and Wright, S. (editors): Intelligent Spaces - The Application of Pervasive ICT. Springer, London, UK, 2006.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Search process

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Selection process; Information filtering

  K. Computing Milieux
  K.4 COMPUTERS AND SOCIETY
      K.4.2 Social Issues
          Subjects: Assistive technologies for persons with disabilities

General Terms:
Experimentation, Human Factors, Measurement

Keywords:
assistive technology, data mining, independent living, older adults, visualisation