脑机接口对偏瘫步态改善的影响：研究现状与展望

Effect of Brain-Computer Interface on Gait Improvement in Hemiplegia: Research Status and Prospects

摘要: 脑机接口(BCI)技术为偏瘫患者的步态康复提供了革命性的“意识–控制–反馈”闭环干预新范式。本文系统综述了BCI技术在改善偏瘫步态方面的研究现状、神经机制及未来展望。当前研究主要采用非侵入式BCI (如EEG-BCI)与下肢外骨骼、功能性电刺激等设备相结合，通过解码运动意图驱动设备辅助运动，并同步提供感觉反馈，从而有效促进神经可塑性。临床研究表明，该技术能显著改善慢性期患者的步态参数(如步速、步频和对称性)，Meta分析也证实其对下肢运动功能有积极影响。神经机制研究方面，功能性近红外光谱(fNIRS)和弥散张量成像(DTI)等技术揭示了BCI训练可诱导任务态皮层血氧动力学变化、调节经胼胝体抑制并促进运动网络功能重组与白质纤维束重塑。然而，该领域仍面临非侵入式信号时空分辨率不足、多模态反馈系统个性化适配困难、以及下肢专项研究尤其是高质量随机对照试验(RCT)匮乏等挑战。未来发展方向包括开发柔性外骨骼与多模态生物信号融合技术、建立标准化步态评估体系，并深化神经机制研究与临床转化的结合，以推动BCI技术在步态康复中的精准化和个体化应用。

Abstract: Brain-computer interface (BCI) technology provides a revolutionary new paradigm of “consciousness-control-feedback” closed-loop intervention for gait rehabilitation of hemiplegic patients. This article systematically reviews the research status, neural mechanisms and future prospects of BCI technology in improving hemiplegic gait. Current research mainly uses non-invasive BCI (such as EEG-BCI) combined with lower limb exoskeleton, functional electrical stimulation and other equipment to drive equipment to assist movement by decoding movement intentions and simultaneously providing sensory feedback, thereby effectively promoting neuroplasticity. Clinical studies have shown that this technology can significantly improve gait parameters (such as walking speed, cadence and symmetry) in patients in the chronic phase, and meta-analysis has also confirmed its positive impact on lower limb motor function. In terms of neural mechanism research, technologies such as functional near-infrared spectroscopy (fNIRS) and diffusion tensor imaging (DTI) revealed that BCI training can induce changes in task-state cortical hemodynamics, modulate transcallosal inhibition, and promote functional reorganization of motor networks and remodeling of white matter fiber tracts. However, the field still faces challenges such as insufficient spatiotemporal resolution of non-invasive signals, difficulties in personalized adaptation of multimodal feedback systems, and a lack of specialized research on the lower limbs, especially high-quality randomized controlled trials (RCTs). Future development directions include developing flexible exoskeleton and multi-modal biological signal fusion technology, establishing a standardized gait assessment system, and deepening the combination of neural mechanism research and clinical translation to promote the precise and individualized application of BCI technology in gait rehabilitation.