Estimating Older People’s Physical Functioning with Automated Health Monitoring Technologies at Home: Feature Correlations and Multivariate Analysis

  • Juho Merilahti
  • Juha Pärkkä
  • Ilkka Korhonen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7096)


As person’s functional capacity determines partly one’s independency and quality of life, it should be observed and monitored. We calculated different features from actigraphy, bed sensor, pedometer, weight scale and blood pressure monitor over time period varying between one and two weeks. These features’ connections to typical functional capacity tests such as ADL, balance and muscle strength were studied. No single feature was connected to all the functioning measures which again suggest importance of screening multiple health data sources. Created multivariate model to estimate holistic functional status has statistically significant correlation with ADL and two lower limb muscle strength tests, and almost statistically significant correlation with balance and walk tests.


Physical functioning actigraphy bed sensor pedometer weight scale blood pressure monitor 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Bowling, A., Iliffe, S.: Which model of successful ageing should be used? Baseline findings from a British longitudinal survey of ageing. Age and Ageing 35(6), 607–614 (2006)CrossRefGoogle Scholar
  2. 2.
    Cruz-Jentoft, A.J., Franco, A., Sommer, P., Baeyens, J.P., Jankowska, E., Maggi, A., Ponikowski, P., Ryś, A., Szczerbinska, K., Michel, J.-P., Milewicz, A.: Silver paper: The future of health promotion and preventive actions, basic research, and clinical aspects of age-related disease: A report of the European summit on age-related disease. Aging - Clinical and Experimental Research 21(6), 376–385 (2009)CrossRefGoogle Scholar
  3. 3.
    Cress, M.E.: Assessment of physical performance in older adults. In: Poon, L.W., Chodzko –Zajko, W., Tomporowski, P.D. (eds.) Active Living, Cognitive Functioning, and Aging, HumanKinetics (2006)Google Scholar
  4. 4.
    Masala, C., Petretto, D.R.: From disablement to enablement: Conceptual models of disability in the 20th century. Disability and Rehabilitation 30(17), 1233–1244 (2008)CrossRefGoogle Scholar
  5. 5.
    Karnik, K., Mazzatti, D.J.: Review of tools and technologies to assess multi-system functional impairment and frailty. Clinical Medicine: Geriatrics (3), 1–8 (2009)Google Scholar
  6. 6.
    Carvalho-Bos, S.S., Riemersma-van Der Lek, R.F., Waterhouse, J., Reilly, T., Van Someren, E.J.W.: Strong association of the rest-activity rhythm with well-being in demented elderly women. American Journal of Geriatric Psychiatry 15(2), 92–100 (2007)CrossRefGoogle Scholar
  7. 7.
    Paavilainen, P., Korhonen, I., Lötjönen, J., Cluitmans, L., Jylhä, M., Särelä, A., et al.: Circadian activity rhythm in demented and non-demented nursing-home residents measured by telemetric actigraphy. Journal of Sleep Research 14(1), 61–68 (2005)CrossRefGoogle Scholar
  8. 8.
    Hamilas M, Hämäläinen H, Koivunen M, Lähteenmäki L, Pajala S, Pohjola L.: Toimiva –testit. Iäkkäiden fyysisen toimintakyvyn mittausmenetelmä. Valtiokonttori, report of State Treasure’s test set results (2000),
  9. 9.
    Steffen, T.M., Hacker, T.A., Mollinger, L.: Age- and gender-related test performance in communitydwelling elderly people: six-minute walk test, Berg balance scale, timed up & go test and gaitspeeds. Phys Ther. 82, 128–137 (2002)Google Scholar
  10. 10.
    Lötjönen, J., Korhonen, I., Hirvonen, K., Eskelinen, S., Myllymäki, M., Partinen, M.: Automatic sleep-wake and nap analysis with a new wrist worn online activity monitoring device Vivago WristCare. Sleep 26(1), 86–90 (2003)Google Scholar
  11. 11.
    Merilahti, J., Pärkkä, J., Antila, K., Paavilainen, P., Mattila, E., Malm, E.-J., Saarinen, A., Korhonen, I.: Compliance and technical feasibility of long-term health monitoring with wearable and ambient technologies. Journal of Telemedicine and Telecare 15(6), 302–309 (2009)CrossRefGoogle Scholar
  12. 12.
    Pärkkä, J., Merilahti, J., Mattila, E.M., Malm, E., Antila, K., Tuomisto, M.T., Viljam Saarinen, A., van Gils, M., Korhonen, I.: Relationship of psychological and physiological variables in long-term self-monitored data during work ability rehabilitation program. IEEE Transactions on Information Technology in Biomedicine 13(2), 141–151 (2009)CrossRefGoogle Scholar
  13. 13.
    Merilahti, J., Pärkkä, J., Korhonen, I.: Connections of daytime napping and vigilance measures to activity behaviour and physical functioning. Proceeding (723) Biomedical Engineering (2011)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Juho Merilahti
    • 1
  • Juha Pärkkä
    • 1
  • Ilkka Korhonen
    • 1
  1. 1.VTTTampereFinland

Personalised recommendations