Τρίτη 27 Σεπτεμβρίου 2016

Residual Standard Deviation: Validation of a New Measure of Dual-Task Cost in Below-Knee Prosthesis Users

Publication date: Available online 26 September 2016
Source:Gait & Posture
Author(s): Charla L. Howard, Chris Wallace, James Abbas, Dobrivoje S. Stokic
We developed and evaluated properties of a new measure of variability in stride length and cadence, termed residual standard deviation (RSD). To calculate RSD, stride length and cadence are regressed against velocity to derive the best fit line from which the variability (SD) of the distance between the actual and predicted data points is calculated. We examined construct, concurrent, and discriminative validity of RSD using dual-task paradigm in 14 below-knee prosthesis users and 13 age- and education-matched controls. Subjects walked first over an electronic walkway while performing separately a serial subtraction and backwards spelling task, and then at self-selected slow, normal, and fast speeds used to derive the best fit line for stride length and cadence against velocity. Construct validity was demonstrated by significantly greater increase in RSD during dual-task gait in prosthesis users than controls (group-by-condition interaction, stride length p=0.0006, cadence p=0.009). Concurrent validity was established against coefficient of variation (CV) by moderate-to-high correlations (r=0.50-0.87) between dual-task cost RSD and dual-task cost CV for both stride length and cadence in prosthesis users and controls. Discriminative validity was documented by the ability of dual-task cost calculated from RSD to effectively differentiate prosthesis users from controls (area under the receiver operating characteristic curve, stride length 0.863, p=0.001, cadence 0.808, p=0.007), which was better than the ability of dual-task cost CV (0.692, 0.648, respectively, not significant). These results validate RSD as a new measure of variability in below-knee prosthesis users. Future studies should include larger cohorts and other populations to ascertain its generalizability.



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