The Gait Profile Score and Movement Analysis Profile

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• 作者：Richard Baker ; Jennifer L. McGinley ; Michael H. Schwartz ; Sarah Beynon ; Adam Rozumalski ; H. Kerr Graham ; Oren Tirosh
• 关键词：Gait pathology ; Outcome ; Gait Profile Score ; Gait Deviation Index ; Movement Analysis Profile
• 刊名：Gait and Posture
• 出版年：2009
• 出版时间：October 2009
• 年：2009
• 卷：30
• 期：3
• 页码：265-269
• 全文大小：353 K

文摘

The Gait Deviation Index (GDI) has been proposed as an index of overall gait pathology. This study proposes an interpretation of the difference measure upon which the GDI is based, which naturally leads to the definition of a similar index, the Gait Profile Score (GPS). The GPS can be calculated independently of the feature analysis upon which the GDI is based. Understanding what the underlying difference measure represents also suggests that reporting a raw score, as the GPS does, may have advantages over the logarithmic transformation and z-scaling incorporated in the GDI. It also leads to the concept of a Movement Analysis Profile (MAP) to summarise much of the information contained within kinematic data.

A validation study on all children attending a paediatric gait analysis service over 3 years (407 children) provides evidence to support the use of the GPS through analysis of its frequency distribution across different Gross Motor Function Classification System (GMFCS) and Gillette Functional Assessment Questionnaire (FAQ) categories, investigation of intra-session variability, and correlation with the square root of GGI. Correlation with GDI confirms the strong relationship between the two measures.

The study concludes that GDI and GPS are alternative and closely related measures. The GDI has prior art and is particularly useful in applications arising out of feature analysis such as cluster analysis or subject matching. The GPS will be easier to calculate for new models where a large reference dataset is not available and in association with applications using the MAP.