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. 2013 Jul;38(3):461-5.
doi: 10.1016/j.gaitpost.2013.01.013. Epub 2013 Feb 8.

The gait variability index: a new way to quantify fluctuation magnitude of spatiotemporal parameters during gait

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The gait variability index: a new way to quantify fluctuation magnitude of spatiotemporal parameters during gait

Arnaud Gouelle et al. Gait Posture. 2013 Jul.

Abstract

This article describes a conglomerate measure of gait variability based on nine spatiotemporal parameters: the Gait Variability Index (GVI). Concurrent validity, inter-session reliability and minimum detectable change (MDC) were evaluated in 31 patients with Friedreich's Ataxia (FRDA), through comparisons with classically used evaluation tools such as the International Cooperative Ataxia Rating Scale (ICARS). GVI scores for the healthy population were 100.3±8.6 and were significantly reduced in FRDA patients (70.4±7.9). The GVI was correlated with the global ICARS score and was sensitive enough to differentiate between groups of FRDA patients categorized by the Posture and Gait Disturbances sub-score. The GVI was found to have a high inter-session reliability with an intraclass correlation coefficient of 0.91. A MDC of 8.6 points was found necessary to ensure that a change in GVI reflects a true change rather than measurement error. The GVI provides a quantitative measure of variability which behaves well statistically in both HP and patients with FRDA. It can be easily implemented using the supplemental data provided with this article. Complementary work is necessary to strengthen the GVI validation.

Keywords: CV; FAPS; FRDA; Fluctuation magnitude; Friedreich's Ataxia; Functional Ambulation Performance Score; GDI; GVI; Gait Deviation Index; Gait Variability Index; Gait variability; HP; ICARS; ICARS “Posture and Gait Disturbances” sub-score; ICC; International Cooperative Ataxia Rating Scale; MDC; PCA; PGD; STP; Spatiotemporal parameters; coefficient of variation; healthy population; intraclass correlation coefficient; minimum detectable change; principal component analysis; spatiotemporal parameters.

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