title: Does the evaluation of gait quality during daily life provide insight into fall risk? A novel approach using 3-day accelerometer recordings.
abstract: BACKGROUND
  Many approaches are used to evaluate fall risk. While their properties and performance vary, most reflect performance at a specific moment or are based on subjective self-report.
  
  
  OBJECTIVE
  To quantify fall risk in the home setting using an accelerometer.
  
  
  METHODS
  Seventy-one community-living older adults were studied. In the laboratory, fall risk was assessed using performance-based tests of mobility (eg, Timed Up and Go) and usual walking abilities were quantified. Subsequently, subjects wore a triaxial accelerometer on their lower back for 3 consecutive days. Acceleration-derived measures were extracted from segments that reflected ambulation. These included total activity duration, number of steps taken, and the amplitude and width at the dominant frequency in the power spectral density, that is, parameters reflecting step-to-step variability. Afterwards, self-report of falls was collected for 6 months to explore the predictive value.
  
  
  RESULTS
  Based on a history of 2 or more falls, subjects were classified as fallers or nonfallers. The number of steps during the 3 days was similar (P = .42) in the fallers (7842.1 ± 6135.6) and nonfallers (9055.3 ± 6444.7). Compared with the nonfallers, step-to-step consistency was lower in the fallers in the vertical axis (amplitude fallers, 0.58 ± 0.22 psd; nonfallers, 0.71 ± 0.18 psd; P = .008); in the mediolateral axis, step-to-step consistency was higher in the fallers (P = .014). The 3-day measures improved the identification of past and future falls status (P < .005), compared to performance-based tests.
  
  
  CONCLUSIONS
  Accelerometer-derived measures based on 3-day recordings are useful for evaluating fall risk as older adults perform daily living activities in their everyday home environment.
authors.affiliation: 1Tel-Aviv Sourasky Medical Center, Department of Neurology, Tel-Aviv, Israel.
authors.forename: Aner
authors.initials: A
authors.lastname: Weiss
authors.forename: Marina
authors.initials: M
authors.lastname: Brozgol
authors.forename: Moran
authors.initials: M
authors.lastname: Dorfman
authors.forename: Talia
authors.initials: T
authors.lastname: Herman
authors.forename: Shirley
authors.initials: S
authors.lastname: Shema
authors.forename: Nir
authors.initials: N
authors.lastname: Giladi
authors.forename: Jeffrey M
authors.initials: JM
authors.lastname: Hausdorff
mesh_terms: D061725:Accelerometry; D000058:Accidental Falls / Q000706:statistics & numerical data*; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D005684:Gait; D006801:Humans; D008297:Male; D008991:Monitoring, Physiologic; D018570:Risk Assessment
keywords: accelerometer; activities of daily living; activity monitoring; aging; fall risk; gait; mHealth