Gait Training-Based Motor Imagery and EEG Neurofeedback in Lokomat: A Clinical Intervention With Complete Spinal Cord Injury Individuals

Abstract

Robotic systems, such as Lokomat® have shown promising results in people with severe motor impairments, who suffered a stroke or other neurological damage. Robotic devices have also been used by people with more challenging damages, such as Spinal Cord Injury (SCI), using feedback strategies that provide information about the brain activity in real-time. This study proposes a novel Motor Imagery (MI)-based Electroencephalogram (EEG) Visual Neurofeedback (VNFB) system for Lokomat® to teach individuals how to modulate their own $\mu $ (8-12 Hz) and $\beta $ (15-20 Hz) rhythms during passive walking. Two individuals with complete SCI tested our VNFB system completing a total of 12 sessions, each on different days. For evaluation, clinical outcomes before and after the intervention and brain connectivity were analyzed. As findings, the sensitivity related to light touch and painful discrimination increased for both individuals. Furthermore, an improvement in neurogenic bladder and bowel functions was observed according to the American Spinal Injury Association Impairment Scale, Neurogenic Bladder Symptom Score, and Gastrointestinal Symptom Rating Scale. Moreover, brain connectivity between different EEG locations significantly ( ${p}\lt 0.05$ ) increased, mainly in the motor cortex. As other highlight, both SCI individuals enhanced their $\mu $ rhythm, suggesting motor learning. These results indicate that our gait training approach may have substantial clinical benefits in complete SCI individuals.

Keywords

• Brain connectivity
• spinal cord injury
• neuro-feedback
• gait training
• Lokomat