Objective gait analysis provide a large number of data, which are used for planning further treatment of the patient. Data from groups of patients are used for comparisons of different treatment methods, assessment of the severity of gait deviations, design of classification systems. The Gilette Gait Index (GGI) was designed to express the level of abnormality of the gait pattern of patients with cerebral palsy by one number: a measure of distance between the set of discrete gait parameters of a patient from a similar set of a healthy subject, based on 16 parameters. Gait pathology in other disorders is different, thus other variables may better describe their level of pathology. The aim was to see if modified GGI can be constructed based on other sets of gait variables. To decide which gait variables should be taken three different analytical methods were used: Hellwig Correlation Based Filter, random forest, and correlation methods.

Gait data of 84 patients were retrospectively selected: 30 had spastic cerebral palsy, 24 scoliosis, 30 suffered the stroke.

The results show, that in the final sets of the 16 parameters chosen by the analyses there are some parameters, which were not present in the original list of GGI. If the number of sixteen parameters is kept, there are more than one optimal set of parameters.

In conclusion, the use of analytical methods enabled the choice of sets of 16 gait parameters which are specific for the medical problem, and the calculation of modified GGIs.

客观步态分析可提供大量数据，这些数据可用于计划对患者的进一步治疗。来自患者组的数据用于比较不同的治疗方法，评估步态偏离的严重程度，设计分类系统。吉列特步态指数（GGI）旨在通过一个数字来表达脑瘫患者步态模式的异常水平：一组健康受试者的一组相似的患者离散步态参数之间的距离的量度，基于16个参数。其他疾病的步态病理学有所不同，因此其他变量可能会更好地描述其病理水平。目的是查看是否可以基于其他步态变量集构建修改后的GGI。

回顾性选择84例患者的步态数据：30例发生痉挛性脑瘫，24例脊柱侧弯，30例中风。

结果表明，在通过分析选择的16个参数的最后一组中，有一些参数没有出现在原始GGI列表中。如果保留十六个参数的数量，则有多个以上的最佳参数集。

总之，使用分析方法可以选择针对医学问题的16个步态参数集，并可以计算出修正的GGI。