title: Unobtrusive assessment of mobility.
abstract: This paper describes a model-based approach to the unobtrusive monitoring of elders in their home environment to assess their health, daily activities, and cognitive function. We present a semi-Markov model representation with automated learning to characterize individual elder's mobility in the home environment. The assessed mobility can be used to characterize the elder's speed of walking and can serve as one of the predictors of future cognitive functionality and the ability of elders to live independently in their home environment.
authors.affiliation: Biomed. Eng. Dept., Oregon Health & Sci. Univ., Portland, OR 97239, USA. pavelm@ohsu.edu
authors.forename: Misha
authors.initials: M
authors.lastname: Pavel
authors.forename: Tamara L
authors.initials: TL
authors.lastname: Hayes
authors.forename: Andre
authors.initials: A
authors.lastname: Adami
authors.forename: Holly
authors.initials: H
authors.lastname: Jimison
authors.forename: Jeffrey
authors.initials: J
authors.lastname: Kaye
mesh_terms: D000203:Activities of Daily Living; D000368:Aged; D003071:Cognition; D004777:Environment; D015577:Geriatric Assessment / Q000379:methods*; D005853:Geriatrics / Q000379:methods*; D006299:Health Services for the Aged; D006699:Home Care Services; D006801:Humans; D008390:Markov Chains; D051346:Mobility Limitation; D015233:Models, Statistical; D008962:Models, Theoretical; D009068:Movement; D016138:Walking