Unobtrusive monitoring of the longitudinal evolution of in-home gait velocity data with applications to elder care

Daniel Austin, Tamara L. Hayes, Jeffrey Kaye, Nora Mattek, Misha Pavel

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

Gait velocity has repeatedly been shown to be an important indicator and predictor of both cognitive and physical function, especially in elderly. However, clinical gait assessments are conducted infrequently and cannot distinguish between abrupt changes in function and changes that occur more slowly over time. Collecting gait measurements continuously in-home has recently been proposed and validated to overcome these clinical limitations. In this paper, we describe the longitudinal analysis of in-home gait velocity collected unobtrusively from passive infrared motion sensors. We first describe a model for the probability density function of the in-home gait velocities. We then describe estimation of the evolution of the density function over time and report empirically determined algorithm parameters that have performed well over a wide variety of different gait velocity data. Finally, we demonstrate how this approach allows detection of significant events (abrupt changes in function) and slower changes over time in gait velocity data collected from a sample of two elderly subjects in the Intelligent Systems for Assessing Aging Changes (ISAAC) study.

Original languageEnglish (US)
Title of host publication33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Pages6495-6498
Number of pages4
DOIs
StatePublished - Dec 26 2011
Event33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 - Boston, MA, United States
Duration: Aug 30 2011Sep 3 2011

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Other

Other33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
CountryUnited States
CityBoston, MA
Period8/30/119/3/11

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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  • Cite this

    Austin, D., Hayes, T. L., Kaye, J., Mattek, N., & Pavel, M. (2011). Unobtrusive monitoring of the longitudinal evolution of in-home gait velocity data with applications to elder care. In 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 (pp. 6495-6498). [6091603] (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). https://doi.org/10.1109/IEMBS.2011.6091603