title: Average in-home gait speed: investigation of a new metric for mobility and fall risk assessment of elders.
abstract: A study was conducted to assess how a new metric, average in-home gait speed (AIGS), measured using a low-cost, continuous, environmentally mounted monitoring system, compares to a set of traditional physical performance instruments used for mobility and fall risk assessment of elderly adults. Sixteen participants were recruited from a local independent living facility. In addition to having their gait monitored continuously in their home for an average of eleven months, the participants completed a monthly clinical assessment consisting of a set of traditional assessment instruments: Habitual Gait Speed, Timed-Up and Go, Short Physical Performance Battery, Berg Balance Scale--short form, and Multidirectional Reach Test. A methodology is developed to assess which of these instruments may work well with the largest subset of older adults, is best suited for detecting changes in an individual over time, and most reliably captures the true mobility level of an individual. Using the ability of an instrument to predict how an individual would score on all the instruments as a metric, AIGS performs best, having better predictive ability than the traditional instruments. AIGS also displays the best agreement between observed and smoothed values, indicating it has the lowest intra-individual test-retest variability of the instruments. AIGS, measured continuously, during normal everyday activity, represents a significant shift in assessment methodology compared to infrequently assessed, traditional physical performance instruments. Continuous, in-home data may provide a more accurate and precise picture of the physical function of older adults, leading to improved mobility and fall risk assessment.
authors.affiliation: Department of Electrical and Computer Engineering, University of Missouri - Columbia, 349 Engineering Building West, Columbia, MO 65211, United States. Electronic address: ees6c6@mizzou.edu.
authors.forename: Erik
authors.initials: E
authors.lastname: Stone
authors.affiliation: Department of Electrical and Computer Engineering, University of Missouri - Columbia, United States. Electronic address: skubicm@missouri.edu.
authors.forename: Marjorie
authors.initials: M
authors.lastname: Skubic
authors.affiliation: Sinclair School of Nursing, University of Missouri - Columbia, United States. Electronic address: rantzm@health.missouri.edu.
authors.forename: Marilyn
authors.initials: M
authors.lastname: Rantz
authors.affiliation: Department of Physical Therapy, University of Missouri - Columbia, United States. Electronic address: abbottc@health.missouri.edu.
authors.forename: Carmen
authors.initials: C
authors.lastname: Abbott
authors.affiliation: Sinclair School of Nursing, University of Missouri - Columbia, United States. Electronic address: millerst@missouri.edu.
authors.forename: Steve
authors.initials: S
authors.lastname: Miller
mesh_terms: D000058:Accidental Falls / Q000517:prevention & control*; D000203:Activities of Daily Living; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D005684:Gait / Q000502:physiology*; D015577:Geriatric Assessment / Q000379:methods*; D006801:Humans; D057187:Independent Living; D008297:Male; D015233:Models, Statistical; D018670:Monitoring, Ambulatory / Q000379:methods*; D004856:Postural Balance; D018570:Risk Assessment; D014741:Video Recording
keywords: Elderly; Fall risk; In-home gait; Kinect; Mobility