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<p>Real-time brain-computer interfaces (BCIs) that decode electroencephalograms (EEG) during motor imagery (MI) are powerful adjuncts to rehabilitation after neurotrauma. Further, immersive virtual reality (VR) could complement BCIs by delivering visual and auditory sensory feedback (VR biofeedback) congruent to user’s MI, enabling task-oriented therapies. Yet, therapeutic outcomes rely on user’s proficiency in evoking MI to attain volitional BCI-commanded VR interaction. While previous studies have explored multi-session BCIs, we investigated the impact of longitudinal training on sensorimotor neuromodulation using BCI combined with VR-mediated externally-cued and self-paced lower-limb MI tasks. The EEG-based BCI was coupled with real-time VR biofeedback congruent with the MI task. Over multiple training sessions in laboratory conditions, five unimpaired individuals progressively learnt to improve control over their EEG during MI virtual walking, corresponding with increased BCI classification accuracy. Further, similar improvements were found with four individuals with chronic complete spinal cord injury (SCI) using the system in real-world neurorehabilitation settings. These findings demonstrate that unimpaired and SCI impaired individuals learnt to control their sensorimotor EEG associated with MI tasks through VR-mediated BCI training, which was associated with improved BCI classification accuracy. Our findings highlight the potential of VR-mediated BCIs in enhancing neuromodulation, providing a foundation for future rehabilitation therapies.</p>

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Virtual reality mediated brain-computer interface training improves sensorimotor neuromodulation in unimpaired and post spinal cord injury individuals

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月25日

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  • Malik Muhammad Naeem Mannan,
  • Dinesh B. Palipana,
  • Kyle Mulholland,
  • Evan Jurd,
  • Ewan C. R. Lloyd,
  • Alastair R. J. Quinn,
  • Claire B. Crossley,
  • Mohammad Fazle Rabbi,
  • David G. Lloyd,
  • Yang D. Teng,
  • Claudio Pizzolato

摘要

Real-time brain-computer interfaces (BCIs) that decode electroencephalograms (EEG) during motor imagery (MI) are powerful adjuncts to rehabilitation after neurotrauma. Further, immersive virtual reality (VR) could complement BCIs by delivering visual and auditory sensory feedback (VR biofeedback) congruent to user’s MI, enabling task-oriented therapies. Yet, therapeutic outcomes rely on user’s proficiency in evoking MI to attain volitional BCI-commanded VR interaction. While previous studies have explored multi-session BCIs, we investigated the impact of longitudinal training on sensorimotor neuromodulation using BCI combined with VR-mediated externally-cued and self-paced lower-limb MI tasks. The EEG-based BCI was coupled with real-time VR biofeedback congruent with the MI task. Over multiple training sessions in laboratory conditions, five unimpaired individuals progressively learnt to improve control over their EEG during MI virtual walking, corresponding with increased BCI classification accuracy. Further, similar improvements were found with four individuals with chronic complete spinal cord injury (SCI) using the system in real-world neurorehabilitation settings. These findings demonstrate that unimpaired and SCI impaired individuals learnt to control their sensorimotor EEG associated with MI tasks through VR-mediated BCI training, which was associated with improved BCI classification accuracy. Our findings highlight the potential of VR-mediated BCIs in enhancing neuromodulation, providing a foundation for future rehabilitation therapies.