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Moving forward on gait measurement: Toward a more refined approach
Journal article   Peer reviewed

Moving forward on gait measurement: Toward a more refined approach

S. Lord, B. Galna and L. Rochester
Movement Disorders, Vol.28(11), pp.1534-1543
2013
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Abstract

Gait is emerging as a powerful measurement tool in neurodegenerative disorders to identify markers of incipient pathology, inform diagnostic algorithms and disease progression, and measure the efficacy of interventions. However, it is unclear which of the many gait outcomes is most appropriate for each of these purposes. In this review, we summarise key topics relating to gait measurement. We draw on literature from Parkinson's disease, ageing, and neurodegenerative disease to address the issue of variable selection with the goal of moving toward a structured approach to measurement. Findings from this review identify a wide range of spatiotemporal and dynamic characteristics; however, their suitability differs according to the aim of measurement. Gait speed is useful as a global characteristic of performance but may not capture the nature of underlying pathology. Inconsistent application, reporting, and interpretation of gait outcomes currently preclude a prescriptive approach. Conceptual models of gait may facilitate a reasoned approach to outcome selection. We also recommend harmonisation of protocols, longitudinal cohort studies, and use of novel technologies and methods of analysis to provide a complete picture of gait. Gait characteristics are “fit for purpose” when selected according to a clear rationale and in accordance with their clinimetric properties. Evidence supports the use of gait as a biomarker of disease and to complement diagnosis and inform disease management. A structured approach to measurement is urgently required to fully realise the contribution gait can make to our understanding of neurodegenerative disease.

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Citation topics
1 Clinical & Life Sciences
1.82 Gait & Posture
1.82.263 Gait and Balance
Web Of Science research areas
Clinical Neurology
ESI research areas
Neuroscience & Behavior
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