Why should 3D Gait Analysis be included in the Walking Pattern Assessment of individuals with Spinal Cord Injury? : Biomechanical analysis of gait and gait patterns in individuals with spinal cord injury

Abstract: Background: The yearly incidence of people with Spinal Cord Injury (SCI) is between250,000 and 500,000, according to the World Health Organization (WHO). The injury often reduces the ability to walk. Various consequences affect the nervous system and, thus, the entire body. Therefore, the patient population with SCI is highly heterogeneous also in their gait patterns. Multiple tools are used to classify and understand the walking impairments caused by the injury. Objective: To underline the added value brought by the integration of 3D gait analysis to more standard methods (GDI, GPS, GVS, spatiotemporal parameters, ASIAgrade, muscle strength, and spasticity) in the evaluation and interpretation of gait patterns of subjects with SCI. Methods: 3D gait analysis with a passive optical motion capture system (Vicon)and four force plates was performed in 7 control subjects and 3 with SCI. The model used for marker placement and pre-processing was CGM 2.3. Matlab was used to analyze and plot the kinematic and kinetic joints’ data and calculate the GDI, GPS, and GVS indexes and spatiotemporal parameters for subjects with SCI and the control group. A specialized physiotherapist conducted the clinical assessment of the patients with SCI in a rehabilitation center. This included: ASIA grade and review, muscle strength, and spasticity with Daniels Whorthingham scale and Modified Ashworth scale, respectively. The evaluation of the result was qualitative. Results: The integration of 3D gait analysis show further understanding in the assessment of walking impairments. The indexes resumed the impairments and classified the subjects but lacked temporal and functional perspective. Gait phases and spatiotemporal parameters suggested difficulties in stability and balance but could not identify the problem’s origin. Lastly, clinical assessment enlightened the singular motor and sensory function impairments. 3D gait analysis contextualized these results identifying gait patterns and functional implications. Conclusion: Integrating 3D gait analysis might give a deeper understanding of subjects with SCI’s gait strategies and impairments. Indeed this complex technique links the other methods’ results, contextualizing them and gaining information.