Model-based inference of cognitive processes from unobtrusive gait velocity measurements

Daniel Austin, Todd Leen, Tamara L. Hayes, Jeffrey Kaye, Holly Jimison, Nora Mattek, Misha Pavel

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

4 Citations (Scopus)

Abstract

In this paper we describe a preliminary modeling and analysis of a unique data set comprising unobtrusive and continuous measurements of gait velocity in the elder participants' residences. The data have been collected as a part of a longitudinal study aimed at early detection of cognitive decline. We motivate these analyses by first presenting evidence that suggests significant relationship between gait parameters and cognitive functions. We then describe a simple, modelbased approach to the analysis of gait velocity using a weighted correlation function estimates. One of the main challenges is due to the fact that the daily estimates of the gait parameters vary with the number of walks. We illustrate the importance of using weighted as opposed to unweighted estimates on a sample of different houses. The correlation functions appear to capture behavioral differences that can be related to the cognitive functioning of the participants.

Original languageEnglish (US)
Title of host publication2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
Pages5230-5233
Number of pages4
DOIs
StatePublished - 2010
Event2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 - Buenos Aires, Argentina
Duration: Aug 31 2010Sep 4 2010

Other

Other2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
CountryArgentina
CityBuenos Aires
Period8/31/109/4/10

Fingerprint

Velocity measurement

ASJC Scopus subject areas

  • Biomedical Engineering

Cite this

Austin, D., Leen, T., Hayes, T. L., Kaye, J., Jimison, H., Mattek, N., & Pavel, M. (2010). Model-based inference of cognitive processes from unobtrusive gait velocity measurements. In 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 (pp. 5230-5233). [5626276] https://doi.org/10.1109/IEMBS.2010.5626276

Model-based inference of cognitive processes from unobtrusive gait velocity measurements. / Austin, Daniel; Leen, Todd; Hayes, Tamara L.; Kaye, Jeffrey; Jimison, Holly; Mattek, Nora; Pavel, Misha.

2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10. 2010. p. 5230-5233 5626276.

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

Austin, D, Leen, T, Hayes, TL, Kaye, J, Jimison, H, Mattek, N & Pavel, M 2010, Model-based inference of cognitive processes from unobtrusive gait velocity measurements. in 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10., 5626276, pp. 5230-5233, 2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10, Buenos Aires, Argentina, 8/31/10. https://doi.org/10.1109/IEMBS.2010.5626276
Austin D, Leen T, Hayes TL, Kaye J, Jimison H, Mattek N et al. Model-based inference of cognitive processes from unobtrusive gait velocity measurements. In 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10. 2010. p. 5230-5233. 5626276 https://doi.org/10.1109/IEMBS.2010.5626276
Austin, Daniel ; Leen, Todd ; Hayes, Tamara L. ; Kaye, Jeffrey ; Jimison, Holly ; Mattek, Nora ; Pavel, Misha. / Model-based inference of cognitive processes from unobtrusive gait velocity measurements. 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10. 2010. pp. 5230-5233
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