Hybrid EEG–EOG Brain–Computer Interface for Virtual-Reality Powered Mobility Training in Children with Severe Neuromotor Disabilities: A Multiple-Case Feasibility Study
Authors:
- Kevin MarcacciniKevin Marcaccini
- Francesca PulvirentiFPFrancesca Pulvirenti
- Francesco PierottiFPFrancesco Pierotti
- Laura DellaroleLDLaura Dellarole
- Marzia BiancoMBMarzia Bianco
- Giulia PiermariaGPGiulia Piermaria
- Francesca TampelliniFTFrancesca Tampellini
- Serena MoscatoSMSerena Moscato
- Luca ToninLuca Tonin
- Stefano TortoraStefano Tortora
- Lorenzo ChiariLorenzo Chiari
- Antonella CersosimoACAntonella Cersosimo
Preprint
- 17 September 2026
- preprint
- Published by MDPI AG in Preprints.org
Abstract
Background: Developing Brain–Computer Interfaces (BCIs) for children with severe neuromotor disabilities remains challenging due to developmental neurophysiology and the high cognitive demands of motor imagery. Hybrid BCIs integrating electroencephalography (EEG) and electrooculography (EOG) can overcome these limitations by combining continuous motor-related control with reliable discrete commands. This multiple-case study investigated the feasibility of a hybrid EEG–EOG BCI integrated with a virtual reality (VR) powered-wheelchair simulator for mobility training. Methods: Six participants (one child, five adolescents) with severe neuromotor disabilities completed repeated sessions using a self-paced BCI. The system combined continuous kinesthetic motor imagery (KMI) for steering and EOG-detected voluntary blinks for discrete commands. We evaluated online classification performance (accuracy, sensitivity, specificity), user workload (NASA-TLX), and simulator-related discomfort (MSAQ) under fully and semi-immersive VR conditions. Results: Despite expected inter-subject variability, most participants achieved functional online VR wheelchair control, reaching a mean accuracy of 77% in successful sessions with balanced sensitivity and specificity. NASA-TLX scores indicated moderate cognitive workload but consistently low frustration. Zero dropouts and low MSAQ scores demonstrated excellent protocol tolerability, high engagement, and minimal cybersickness across both VR modalities. Conclusions: This study demonstrates the feasibility of combining hybrid EEG–EOG BCI control with VR for pediatric powered mobility training. The framework enabled functional control with high usability and minimal adverse effects, supporting the clinical potential of hybrid BCI–VR systems as accessible assistive technologies and providing a foundation for larger clinical trials.Keywords
All Related Versions
- Version 1, 2026-09-17, Preprints
- Published version: Children, 13 (11), 1531.
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