Jul 2026· Theoretical and Natural Science· 0 citations
TL;DR
Analysis of BCI rehabilitation technologies shows that each paradigm has its own advantages for different patient groups, and future research directions including intelligent adaptive optimization, hybrid system integration, remote rehabilitation, unified evaluation criteria and large-scale clinical trials can help the clinical translation of BCI rehabilitation technologies.
Abstract
Stroke is a main reason for long-term disability globally, motor and cognitive impairments appear after stroke, which can reduce quality of life for patients and makes the rehabilitation process become more complex, new auxiliary tools are needed. Non-invasive brain-computer interfaces (BCIs) are promising tools to help stroke rehabilitation. BCI combined with functional electrical stimulation (BCI-FES) is used in many studies. Transcranial electrical stimulation-assisted BCI (BCI-TES) is another method. Virtual reality-integrated BCI (BCI-VR) shows good potential. This paper analysis the working mechanisms, clinical efficacy and limitations of these methods, and then multidimensional comparison is conducted which covers applicable populations, user tolerance, equipment performance and also the clinical evidence from existing studies to give full picture of current status. The results show that each paradigm has its own advantages for different patient groups. BCI-FES can help muscle reanimation for severe paresis. BCI-TES is expected to enhance cortical excitability in the early subacute stage. BCI-VR provides immersive task training, which can improve rehabilitation outcomes for mild impairments. It is stratified and phase-adaptive, and can guide the combination of individualized modalities and sequential intervention across stroke recovery stages. Future research directions including intelligent adaptive optimization, hybrid system integration, remote rehabilitation, unified evaluation criteria and large-scale clinical trials, and these efforts can help the clinical translation of BCI rehabilitation technologies so that more patients can benefit from these new methods in hospitals and home settings.
The study stresses the necessity of embedding relational autonomy and neural rights into BCI development, tying technological trajectories to governance demands in order to shape responsible paths for future neurotechnologies.
Yuzhang Wu· Theoretical and Natural Scie...· 0 citations
Non-invasive EEG-based Brain–Computer Interface (BCI), when used alongside conventional physiotherapy and other rehabilitation approaches such as functional electrical stimulation, robotic-assisted therapy, and virtual reality, was associated with improved upper-limb motor function, motor control, functional independence, and neuroplasticity in individuals with stroke.
kumar S Anil, B. Sharvani, M. H· World Journal of Advanced Re...· 0 citations
The neurophysiological basis of EEG-BCI and three major rehabilitation paradigms are outlined, including motor imagery with physical feedback, motor imagery with virtual/multisensory feedback, and the steady-state visual evoked potential (SSVEP)-driven paradigm.
Wang Peng, Yang Yang, Juehan Wang et al.· Topics in Stroke Rehabilitat...· 0 citations
The combination of visual-guided BCI and FES may represent a promising adjunctive rehabilitation approach for stroke patients with severe motor impairment, particularly for those who are unable to actively participate in conventional rehabilitation.
Y. E. Doğan· Acupuncture & Electro-Th...· 0 citations
Overall, the certainty of evidence was low to very low, downgraded primarily for these risk of bias concerns, severe imprecision (due to small sample sizes), and potential publication bias.
Yu Qin, Mei-xuan Li, Yan-fei Li et al.· Cochrane Database of Systema...· 0 citations
With the continuous development of artificial intelligence, novel biomaterials, and immersive technologies such as virtual reality, BCIs are expected to evolve toward more personalized, home-based, and intelligent rehabilitation solutions, accelerating their clinical application and offering new therapeutic hope for SCI patients.
Xudong Zhao, Keyi Chen, Jinquan Ma et al.· Spine Research· 0 citations
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