title: Gait variability and stability measures: minimum number of strides and within-session reliability.
abstract: BACKGROUND
  Several methods are proposed in the literature for the quantification of gait variability/stability from trunk accelerations. Since outputs can be influenced by implementation differences, reliability assessment and standardization of implementation parameters are still an issue. The aim of this study is to assess the minimum number of required strides and the within-session reliability of 11 variability/stability measures.
  
  
  METHODS
  Ten healthy participants walked in a straight line at self-selected speed wearing two synchronized tri-axial Inertial Measurement Units. Five variability measures were calculated based on stride times namely Standard deviation, Coefficient of variation, Inconsistency of variance, Nonstationary index and Poincaré plot. Six stability measures were calculated based on trunk accelerations namely Maximum Floquet multipliers, Short term/long term Lyapunov exponents, Recurrence quantification analysis, Multiscale entropy, Harmonic ratio and Index of harmonicity. The required minimum number of strides and the within-session reliability for each measure were obtained based on the interquartile range/mean ratio. Measures were classified in five categories (namely excellent, good, average, poor, and very poor) based on their reliability.
  
  
  RESULTS
  The number of strides required to obtain a reliable measure was generally larger than those conventionally used. Variability measures showed average to poor reliability, while stability measures ranged from excellent to very poor reliability.
  
  
  CONCLUSIONS
  Recurrence quantification analysis and multiscale entropy of trunk accelerations showed excellent reliability and a reasonable number of required strides. Based on these results, these measures should be taken into consideration in the assessment of fall risk.
authors.affiliation: DEI - Department of Electrical, Electronic, and Information Engineering 'Guglielmo Marconi', University of Bologna, via Venezia 52, 47521 Cesena (FC), Italy. Electronic address: f.riva@unibo.it.
authors.forename: F
authors.initials: F
authors.lastname: Riva
authors.affiliation: DEI - Department of Electrical, Electronic, and Information Engineering 'Guglielmo Marconi', University of Bologna, via Venezia 52, 47521 Cesena (FC), Italy.
authors.forename: M C
authors.initials: MC
authors.lastname: Bisi
authors.affiliation: DEI - Department of Electrical, Electronic, and Information Engineering 'Guglielmo Marconi', University of Bologna, via Venezia 52, 47521 Cesena (FC), Italy; Health Sciences and Technologies - Interdepartmental Center for Industrial Research (HST - ICIR), University of Bologna, Italy.
authors.forename: R
authors.initials: R
authors.lastname: Stagni
mesh_terms: D000054:Acceleration; D000328:Adult; D000465:Algorithms; D001696:Biomechanical Phenomena; D003198:Computer Simulation; D005684:Gait; D064368:Healthy Volunteers; D006801:Humans; D018670:Monitoring, Ambulatory / Q000295:instrumentation; D015203:Reproducibility of Results; D060726:Torso; D016138:Walking
keywords: Gait stability; Gait variability; Inertial sensors; Stride number; Within-session reliability