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首页> 美国卫生研究院文献>Frontiers in Human Neuroscience >Current State and Future Prospects of EEG and fNIRS in Robot-Assisted Gait Rehabilitation: A Brief Review
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Current State and Future Prospects of EEG and fNIRS in Robot-Assisted Gait Rehabilitation: A Brief Review

机译：脑电图和fNIRS在机器人辅助步态康复中的现状和未来展望：简要回顾

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Gait and balance impairments are frequently considered as the most significant concerns among individuals suffering from neurological diseases. Robot-assisted gait training (RAGT) has shown to be a promising neurorehabilitation intervention to improve gait recovery in patients following stroke or brain injury by potentially initiating neuroplastic changes. However, the neurophysiological processes underlying gait recovery through RAGT remain poorly understood. As non-invasive, portable neuroimaging techniques, electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) provide new insights regarding the neurophysiological processes occurring during RAGT by measuring different perspectives of brain activity. Due to spatial information about changes in cortical activation patterns and the rapid temporal resolution of bioelectrical changes, more features correlated with brain activation and connectivity can be identified when using fused EEG-fNIRS, thus leading to a detailed understanding of neurophysiological mechanisms underlying motor behavior and impairments due to neurological diseases. Therefore, multi-modal integrations of EEG-fNIRS appear promising for the characterization of neurovascular coupling in brain network dynamics induced by RAGT. In this brief review, we surveyed neuroimaging studies focusing specifically on robotic gait rehabilitation. While previous studies have examined either EEG or fNIRS with respect to RAGT, a multi-modal integration of both approaches is lacking. Based on comparable studies using fused EEG-fNIRS integrations either for guiding non-invasive brain stimulation or as part of brain-machine interface paradigms, the potential of this methodologically combined approach in RAGT is discussed. Future research directions and perspectives for targeted, individualized gait recovery that optimize the outcome and efficiency of RAGT in neurorehabilitation were further derived.
机译：步态和平衡障碍经常被视为神经病患者最关注的问题。机器人辅助步态训练（RAGT）已被证明是一种有前途的神经康复干预措施，可通过潜在地引发神经塑性改变来改善中风或脑损伤后患者的步态恢复。然而，通过RAGT恢复步态的神经生理过程仍然知之甚少。作为非侵入性便携式神经成像技术，脑电图（EEG）和功能性近红外光谱（fNIRS）通过测量大脑活动的不同视角，为RAGT期间发生的神经生理过程提供了新见解。由于有关皮质激活模式变化的空间信息以及生物电变化的快速时间分辨率，使用融合的EEG-fNIRS可以识别与大脑激活和连通性相关的更多功能，从而使人们对运动行为和神经系统疾病引起的损伤。因此，EEG-fNIRS的多模式整合似乎有望在RAGT诱导的脑网络动力学中表征神经血管耦合。在这篇简短的评论中，我们调查了专门针对机器人步态康复的神经影像研究。尽管先前的研究已经针对RAGT检验了EEG或fNIRS，但仍缺乏两种方法的多模式整合。基于可融合的EEG-fNIRS融合技术（用于指导非侵入性脑刺激或作为脑机接口范例的一部分）的可比研究，讨论了该方法学结合方法在RAGT中的潜力。进一步得出了针对性，个体化步态恢复的未来研究方向和观点，这些步伐和恢复可优化RAGT在神经康复中的结果和效率。

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