Estimating Older People's Physical Functioning with Automated Health Monitoring technologies at home: Feature correlations and multivariate analysis

Juho Merilahti, Juha Pärkkä, Ilkka Korhonen

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

Abstract

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
Original languageEnglish
Title of host publicationRautiainen M. et al. (eds) Grid and Pervasive Computing Workshops. GPC 2011. Lecture Notes in Computer Science, vol 7096. Springer
PublisherSpringer
Pages94-104
ISBN (Electronic)978-3-642-27916-4
Publication statusPublished - 2011
MoE publication typeA4 Article in a conference publication
EventInternational Conference on Grid and Pervasive Computing, GPC 2011: International Workshops - Oulu, Finland
Duration: 11 May 201113 May 2011

Publication series

SeriesLecture Notes in Computer Science
Volume7096

Conference

ConferenceInternational Conference on Grid and Pervasive Computing, GPC 2011
Abbreviated titleGPC 2011
CountryFinland
CityOulu
Period11/05/1113/05/11

Keywords

  • Physical functioning
  • actigraphy
  • bed sensor
  • pedometer
  • weight scale
  • blood pressure monitoring

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    Merilahti, J., Pärkkä, J., & Korhonen, I. (2011). Estimating Older People's Physical Functioning with Automated Health Monitoring technologies at home: Feature correlations and multivariate analysis. In Rautiainen M. et al. (eds) Grid and Pervasive Computing Workshops. GPC 2011. Lecture Notes in Computer Science, vol 7096. Springer (pp. 94-104). Springer. Lecture Notes in Computer Science, Vol.. 7096 https://doi.org/10.1007/978-3-642-27916-4_11