EEG Neurofeedback-Based Gait Motor Imagery Training in Lokomat Enhances Motor Rhythms in Complete Spinal Cord Injury
Robotic interventions combining neurofeedback (NFB) and motor imagery (MI) are emerging strategies to promote cortical reorganization and functional training in individuals with complete spinal cord injury (SCI). This study proposes an electroencephalogram-based NFB approach for MI training, designed to teach the MI-related brain rhythmics modulation in Lokomat. For the purposes of this study, NFB is defined as a visual feedback training scheme. The proposed system introduces a formulation to minimize the default cortical effects that Lokomat produces on the individual’s activity during passive walking. Two individuals with complete SCI tested the proposed NFB system, in order to relearn the modulation of Mu (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula> : 8–12 Hz) and Beta (<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\beta$</tex-math></inline-formula> : 13–30 Hz) rhythms over Cz, while receiving gait training with full weight support across 12 sessions. Each session consisted of the following three stages: 1) 2 min walking without MI (baseline); 2) 5 min walking with MI and True NFB; and 3) 5 min walking with MI and Sham NFB. The latter two stages were randomized session-by-session. The findings suggest that the proposed NFB approach may promote cortical reorganization and support the restoration of sensorimotor functions. Significant differences were observed between cortical patterns during True NFB and Sham NFB, particularly in the last intervention sessions. These results confirm the positive impact of the NFB system on gait motor training by enabling individuals with complete SCI to learn how to modulate their motor rhythms in specific cortical areas.
Institutions
- Universidade Federal do Espírito Santo (BR)
Publication Details
- Journal
- IEEE Transactions on Human-Machine Systems
- Published
- 2025-09-12
- DOI
- https://doi.org/10.1109/thms.2025.3603548
- Primary Topic
- Geochemistry and Geologic Mapping
- Type
- article
- Field-Weighted Citation Impact
- 0.00