The Gait Deviation Index (GDI) is a multivariate measure of overall gait pathology based on 15 gait features derived from three-dimensional (3D) kinematic data. GDI aims at providing a comprehensive, easy to interpret, and clinically meaningful metric of overall gait function. It has been used as an outcome measure to study gait in several conditions: cerebral palsy (CP), post-stroke hemiparetic gait, Duchenne muscular dystrophy, and Parkinson’s disease, among others. Nevertheless, its use in population with Spinal Cord Injury (SCI) has not been studied yet. The aim of the present study was to investigate the applicability of the GDI to SCI through the assessment of the relationship of the GDI with the Walking Index for Spinal Cord Injury (WISCI) II. 3D gait kinematics of 34 patients with incomplete SCI (iSCI) was obtained. Besides, 3D gait kinematics of a sample of 50 healthy volunteers (HV) was also gathered with Codamotion motion capture system. A total of 302 (iSCI) and 446 (HV) strides were collected. GDI was calculated for each stride and grouped for each WISCI II level. HV data were analyzed as an additional set. Normal distribution for each group was assessed with Kolmogorov-Smirnov tests. Afterward, ANOVA tests were performed between each pair of WISCI II levels to identify differences among groups (p < 0.05). The results showed that the GDI was normally distributed across all WISCI II levels in both iSCI and HV groups. Furthermore, our results showed an increasing relationship between the GDI values and WISCI II levels in subjects with iSCI, but only discriminative in WISCI II levels 13, 19, and 20. The index successfully distinguished HV group from all the individuals with iSCI. Findings of this study indicated that the GDI is not an appropriate multivariate walking metric to represent the deviation of gait pattern in adult population with iSCI from a normal gait profile when it is compared with the levels of walking impairment described by the WISCI II. Future work should aim at defining and validating an overall gait index derived from 3D kinematic gait variables appropriate for SCI, additionally taking into account other walking ability outcome measures.

The Gait Deviation Index (GDI) is a dimensionless multivariate measure of overall gait pathology represented as a single score that indicates the gait deviation from a normal gait average. It is calculated using kinematic data recorded during a three-dimensional gait analysis and an orthonormal vectorial basis with 15 gait features that was originally obtained using singular value decomposition and feature analysis on a dataset of children with cerebral palsy. Ever since, it has been used as an outcome measure to study gait in several conditions, including spinal cord injury (SCI). Nevertheless, the validity of implementing the GDI in a population with SCI has not been studied yet. We investigate the application of these mathematical methods to derive a similar metric but with a dataset of adults with SCI (SCI-GDI). The new SCI-GDI is compared with the original GDI to evaluate their differences and assess the need for a specific GDI for SCI and with the WISCI II to evaluate its sensibility. Our findings show that a 21-feature basis is necessary to account for most of the variance in gait patterns in the SCI population and to provide high-quality reconstructions of the gait curves included in the dataset and in foreign data. Furthermore, using only the first 15 features of our SCI basis, the fidelity of the reconstructions obtained in our population is higher than that when using the basis of the original GDI. The results showed that the SCI-GDI discriminates most levels of the WISCI II scale, except for levels 12 and 18. Statistically significant differences were found between both indexes within each WISCI II level except for 12, 20, and the control group (p < 0.05). In all levels, the average GDI value was greater than the average SCI-GDI value, but the difference between both indexes is larger in data with greater impairment and it reduces progressively toward a normal gait pattern. In conclusion, the implementation of the original GDI in SCI may lead to overestimation of gait function, and our new SCI-GDI is more sensitive to larger gait impairment than the GDI. Further validation of the SCI-GDI with other scales validated in SCI is needed.